A different conception of the nutritional quality of foods, and the language that can be used to describe it, is presented below.

Note that this conception is not by any means the only one possible (indeed, the fact that there are many different ideas about what is meant by a nutrient dense/healthy/healthful food contributes to the confusion surrounding the terms).

Our conception places all foods onto a continuous spectrum ranging from ‘most healthful’ to ‘least healthful’ (or ‘most unhealthful’).

Within this spectrum, it is possible to compare any two foods, or any two sets of foods.

Figure 1 provides an illustration of this concept and shows how ‘stewed apple with sugar’ is considered less healthful than ‘stewed apple’, and how ‘high-fat beef sausage’ is considered less healthful than ‘low-fat beef sausage’, but both sausages are considered less healthful than both stewed apples with or without sugar.

Note that the mechanisms used to measure the healthfulness of each food (e.g. the nutrients to include, the unit of measurement to use) are not yet relevant – it is the concept of the continuum of healthfulness that is important here.


We prefer the word ‘healthful’ (and ‘healthfulness’) rather than ‘healthy’ (and ‘healthiness’) as foods do not develop disease so it does not make sense to describe a food as healthy.

We acknowledge that diets also do not develop disease, so it is anomalous to describe diets as healthy – we do so here to avoid conflicting terms.

The ‘correct’ order of the foods on the spectrum is dependent on how the spectrum is to be used.

For this illustration, we are defining a healthful food as one that, when consumed, makes the total diet more healthy (and the greater the contribution to healthiness of the diet the more healthful the food is).

For this reason, we have placed water in the middle of the spectrum representing that it makes neither a positive nor a negative contribution to the healthiness of the diet (note that for different spectrums water will be placed in different places – if the spectrum is based purely on the presence of beneficial nutrients then water will not be considered healthful.

If based purely on the absence of nutrients to be limited then water will be considered healthful).


Note our concept of a healthful food is not a food that is likely to contribute to a healthy diet.

Foods are eaten in patterns and combinations that can result in apparent anomalies in the comparison of healthful foods with healthy diets.

For example, as Nicklas et al. point out [1], high-sugar breakfast cereals are often found to be components of a healthy diet [3], and they therefore argue that breakfast cereals should be defined as ‘nutrient dense’.

We disagree.

There are many foods that are likely to be found to be a part of a healthy diet that have little to do with their nutritional quality but are due to the combinations in which they are eaten.

For example, salad dressing is often a part of a healthy diet because it is eaten with salad rather than because it is healthful in and of itself.

In our conception, high-sugar breakfast cereals are not defined as healthful as when consumed they make a (generally healthy) diet less healthy.


A couple of important points should be made explicit here.

First, whether or not high-sugar breakfast cereals make total diets more or less healthy is entirely dependent upon the weight placed on beneficial nutrients and nutrients to be limited, whether fortificants are included in the calculations, etc.

This is all well covered in the article by Nicklas and colleagues [1].

Second, high-sugar cereals may be more healthful than some breakfast alternatives (e.g. a croissant and chocolate spread), but still not healthful per se.

This is allowed by our conception of a continuum of healthfulness, but may not be allowed by other conceptions that are based on comparisons of foods.


What is (and isn’t) nutrient profiling?


Once a robust conception of ‘healthfulness’ is agreed, the next stage is to operationalise this conception.

One way of doing this is to group foods into categories and to distribute the categories along the continuum with (for example) fruits more healthful than chocolates.

While this may be good enough for many purposes it is an unsatisfactory representation of the conception that we have built, as there is no room for differences within food categories and the positioning of food categories along the spectrum is arbitrary, leading to a ranking of food categories rather than a continuous scale.

We need a process that unambiguously places each food at a single point on the continuum based on some predefined criteria, and this is one of the things that a nutrient profile model can do.


A nutrient profile model is defined by the WHO as a set of equations or algorithms that ‘categorise foods for the purpose of health on the basis of their nutritional properties’ [4].

The key points here that define nutrient profile models are that they must only use information about a food in isolation (i.e. they do not take account of how often the food is consumed, in what context or in combination with what other foods) and they are specifically concerned with health.

Therefore a model that aims to regulate health claims on high-fat, -salt or -sugar products by using a score for all foods on the basis of their fat, sugar and salt levels is a nutrient profile model; a model that estimates a ‘sustainability score’ on the basis of their carbon, water and land footprint is not a nutrient profile model; and a model that generates a score for a food based on the probability that the food is consumed in a sub-sample of a population that consumes a healthy diet is not a nutrient profile model.


There are at least two questions relating to this definition of a nutrient profile model.

First, does the definition allow for nutrient profile models that measure nutrients on a per serving basis?

This depends on whether ‘serving size’ is considered to be a property of a food.

This is hard to justify since so many foods are eaten in very different serving sizes depending on context (e.g. milk as a drink has a large serving size but as an addition to coffee has a small serving size).

A strict reading of the definition would therefore suggest that nutrient profile models should not use a per serving basis, but in practice many nutrient profile models use this measurement and it is generally accepted.

Indeed, Nicklas et al. state that ‘[a] challenge [for defining nutrient density] is to identify a standard unit that reflects a reasonable serving for some foods and is a concept that consumers can understand’ [1].

We think that nutrient profile models are best suited to comparing the nutritional quality of foods (irrespective of the serving size they are consumed in) and considerations of how important the nutrient profile scores are for foods that are eaten in large or small quantities should be left to the users of the nutrient profile model.


Second, how should ‘a food’ be defined? In most cases this is unproblematic, but in some cases foods are rarely if ever eaten in the form that they are sold (e.g. flour, dried pasta, instant drinking chocolate, breakfast cereal).

Here it is necessary for each nutrient profile model to explicitly state whether the model should be applied to foods as sold or foods as consumed, and if the latter then how these consumed foods should be constructed.


Nutrient profile models can provide a precise score representing the healthfulness of all foods, but this precision can be deceptive.

What do the nutrient profile scores mean? They are based on many decisions and assumptions; for example, which nutrients should be included in the model, what weighting should be placed on each nutrient.

These decisions have been detailed elsewhere [1, 5].

It has been shown that different nutrient profile models sometimes agree and sometimes do not agree with each other [6, 7].

This may be because the nutrient profile models are based on different conceptions of ‘healthfulness’ (e.g. one based on the presence of health-promoting micronutrients such as the Nutrient Value Score (NVS) [8] and one that balances positive and negative nutrients such as the SAIN:LIM score [9]), or because they have been developed in very different ways.

While nutrient profile models can be useful tools for public health regulations, their inherent limitations should not be overlooked.


It is important to separate the nutrient profile model from its application.

For example, the UK Food Standards Agency/Ofcom model that provides a healthfulness score for all foods is used to support the regulation of broadcast advertising of foods to children in the UK [10].

The regulation itself is clearly not a nutrient profile model.

Similarly, the Choices International logo, applied to many food products internationally to identify healthy choices, is supported by a set of nutritional criteria and equations to identify healthy foods [11].

The criteria and equations are a nutrient profile model, whereas the logo itself is not.

This distinction may seem simple, but the confusion between nutrient profile model and application is rife (e.g. Townsend [12]).

In the following section, we discuss applications where nutrient profile models would be helpful and those where they would not.


When nutrient profiling can (and cannot) be useful


A public health intervention could potentially benefit from a nutrient profile model if: (i) it is concerned with improving nutrition; and (ii) it operates on the food level (i.e. it does not take into account information about the diets or health status of individuals).

Some examples of interventions that meet these criteria include: (i) regulation of health claims; (ii) restriction of foods supplied in school vending machines; (iii) criteria for front-of-pack nutrition labelling and health symbols; (iv) health-related food taxes and subsidies; and (v) restriction of marketing of unhealthy foods.


The second criterion here is crucial in uniting these interventions – they are all applied in contexts where individual foods must be considered independent of the context in which they are consumed.

This is not the case for dietary advice, where the aim is to provide advice about foods in the context of how they can combine to create a healthy diet.

In this situation, the context provides more information which a nutrient profile model does not use in its calculations; for example, the combination in which foods are consumed, the need for dietary variety, the context-specific serving size in which foods are consumed, etc.

Nicklas et al. [ 1] describe some unintended consequences associated with using a ‘nutrient density’ approach for dietary advice, including that nutrient-dense foods are often eaten in combination with energy-dense foods, and suggest that to demonise one could affect consumption of the other. They argue that ‘the value of a food should be determined within the context of the whole diet’.

Where this is possible – as in the case of dietary advice – we agree, and given the definition of nutrient profiling provided above, this precludes the use of a nutrient profile model.


Conclusion


There is confusion among policy makers and nutrition academics regarding the role of nutrient profile models.

Much of this confusion is due to the vague definitions of ‘healthy’, ‘healthful’ and ‘nutrient dense’ that are often applied to foods without a complete conception about what is meant by these terms.

Therefore, when a nutrient profile model (which must have an explicit basis for the categorisations or scores that it produces) is compared against these vague definitions, many apparent ‘anomalies’ are found, which may be due to poorly fitting nutrient algorithms but could also be due to the mismatch between different conceptions of ‘healthfulness’.

Nutrient profile models can be useful tools for supporting a large range of public health interventions where only information on the nutritional quality of the food is available.

Where additional information about the role of foods in the overall diet is available, nutrient profile models are less useful.


Although the precise cause of multiple sclerosis remains unknown, various factors have been discovered that de- termine an individual's risk to develop this chronic demyelinating disease of the CNS.

A majority of risk al- leles identified by genome-wide association studies relate to immune functions (Baranzini and Oksenberg, 2017), supporting an autoimmune aetiology for the CNS inflam- mation, demyelination and neurodegeneration that is characteristic of multiple sclerosis.


Environmental factors, such as a symptomatic Epstein-Barr virus (EBV) infection at a vulnerable age (Ascherio and Munger, 2010), smok- ing (Wingerchuk, 2012) as well as lack of sunlight expos- ure (Bjornevik et al., 2014) and low levels of vitamin D (Munger et al., 2006; Ascherio et al., 2010) may also enhance the risk of developing multiple sclerosis.

The latter two factors could be interdependent, as the primary form of vitamin D, cholecalciferol (vitamin D3) is gener- ated in the skin upon ultraviolet (UV) radiation; alterna- tively, vitamin D can be ingested as part of the diet.


While diet is generally considered the minor source of vitamin D (Holick, 2004), it may become essential when UVB exposure is limited (Holick, 1987).

Because vitamin D levels can be effectively and rapidly raised by diet, vita- min D supplementation has gained interest over recent years in multiple sclerosis as well as other chronic conditions.


In general, patients with multiple sclerosis have relatively low levels of vitamin D, which may refer to genetic and metabolic alterations associated with multiple sclerosis itself (Nieves et al., 1994; Laursen et al., 2015; Mokry et al., 2015; Bhargava et al., 2017).

Lower serum concentrations of vitamin D increase the likelihood of both relapses and early onset of disability progression (Runia et al., 2012), whereas levels above 70 nmol/l are associated with a decreased risk for attacks (Smolders et al., 2008).

While these findings clearly highlight low vitamin D levels as a negative predictor in multiple sclerosis, it is currently un- clear whether this association is causal and accordingly, whether therapeutically raising the level of vitamin D in patients with multiple sclerosis is of clinical benefit (Stein et al., 2011; Dorr et al., 2012; Bhargava et al., 2014).


Primarily based on the perception of its harmlessness it is nevertheless current practice to broadly supplement vitamin D in patients with multiple sclerosis, often at excessively high doses.

In light of the current lack of evidence for a clear therapeutic benefit in multiple sclerosis we revisited this concept and investigated the clinical and immunolo- gical effect of chronic vitamin D exposure in the preclinical multiple sclerosis model, murine experimental autoimmune encephalomyelitis (EAE).


Peripheral blood mononuclear cells (PBMCs) were obtained after informed consent.

The protocol was approved by the Ethics committee of the University Medicine of Gö ttingen, ap- proval number 3/4/14.


Wild-type C57BL/6 mice were purchased from Charles River.

MOG p35-55 TCR transgenic 2D2 mice were kindly provided by Dr Kuchroo (Boston, USA).

All animal experiments were carried out in accordance with the guidelines of the Central Department for Animal Experiments, University Medical Center, Gö ttingen and approved by the Office for Consumer Protection and Food Safety of the State of Lower Saxony (protocol number 33.9-42502-04-13/1201, 33.9-42502-04-15/ 1804 and 33.9-42502-04-17/2615).


Female wild-type mice were immunized subcutaneously with 50 mg MOG peptide (p)35-55 MEVGWYRSPFSRVVHLYRNGK (Auspep) emulsified in complete Freund's adjuvant (Sigma- Aldrich) containing 250 mg killed Mycobacterium tuberculosis H37 Ra (BD Bioscience) followed by intraperitoneal injections of 200 ng of Bordetella pertussis toxin (Sigma-Aldrich) on the day of immunization and 2 days thereafter.

EAE severity was assessed daily and scored on a scale from 0 to 5 as follows: 0 = no clinical signs; 1.0 = tail paralysis; 2.0 = hindlimb paresis; 3.0 = severe hindlimb paresis; 4.0 = paralysis of both hindlimbs; 4.5 = hindlimb paralysis and beginning forelimb paresis; and 5.0 = moribund/death.


Mice were fed with a diet containing either low (55 IU/kg food), standard (1500 IU/kg food) or high (75 000 IU/kg food) vitamin D3 concentrations (ssniff Spezialdiaeten) for at least 8 weeks.

These doses were chosen after a dose titration, as they generated serum vitamin D levels reflective of vitamin D defi- ciency (530 nmol/l), physiological vitamin D levels (100 nmol/ l) and continuous high-dose supplementation (250 nmol/l) in patients (Vieth, 1999; Burton et al., 2010; Smolders et al., 2010).

All three diets contained identical calcium (1%) and phosphate (0.7%) concentrations (Supplementary Fig. 1).

Hypercalcaemia in mice was induced by daily intraperitoneal Downloaded from https://academic.oup.com/brain/article/142/9/2737/5532100 by Institut Armand-Frappier user on 16 May 2024 injection of calcium gluconate (2000 mg/kg/day; Sigma- Aldrich) starting 3 days before immunization.


Blood was collected by vein facialis puncture and serum was isolated by centrifugation using gel columns (Sarstedt).

25-OH- vitamin D3 concentrations in serum were measured with liquid chromatography-tandem mass spectrometry using a MassChrom Õ 25-OH-vitamin D3/D2 LC-MS/MS kit (Chromsystems) on an AB Sciex API 4000 LC/MS/MS system (AB Sciex).

Total calcium in serum and culture medium was determined using the Arsenazo III dye binding method on an ARCHITECT c16000 analyser (Abbott Diagnostics).

Ionized calcium in culture medium was measured on a blood gas analyser GEM Premier 4000 (Instrumentation Laboratory).

Total inorganic phosphate in serum was quanti- fied based on Molybdenum blue colorimetric method on an ARCHITECT c16000 analyser (Abbott Diagnostics).

Total sodium in serum and total chloride in culture medium were measured using ion-selective electrodes on an ARCHITECT c16000 analyser (Abbott Diagnostics).


Human PBMCs from healthy donors were isolated after Ficoll gradient centrifugation (Biochrom).

Human T cells were pur- ified from PBMCs by negative magnetic-activated cell sorting (MACS) separation using MojoSort TM human T cell isolation kit (BioLegend).

Single cell suspensions of murine lymphoid tissues were generated by gentle dissection and passing through 70 mm cell strainer (Greiner Bio-One).

Murine CNS mononu- clear cells were isolated by digestion of perfused CNS tissue using collagenase D (Roche) and DNase I (Roche) at 37 C for 45 min.


Mononuclear cells were passed through a 70 mm cell strainer (Greiner Bio-One) and lymphocytes were collected by discontinuous density Percoll Õ gradient (GE Healthcare).

Murine blood was collected in PBS containing 1 mM EDTA followed by erythrocytes lysis using BD Pharm Lysing Buffer.

Murine splenic CD11b + cells were purified by negative MACS separation using a mouse lineage panel (BD Bioscience).

Murine T cells were isolated by negative MACS separation using a mouse pan T cell isolation kit II (Miltenyi).

For sep- arate stimulation of CD4 + and CD8 + T cells, murine T cells were isolated by positive MACS separation using CD4 (L3T4) and CD8a (Ly-2) MicroBeads (Miltenyi), respectively.


Mice were transcardially perfused with PBS followed by 4% paraformaldehyde (PFA) and tissue was paraffin embedded.

One-micrometre thick slices were stained with haematoxylin and eosin and Luxol fast blue/periodic acid shiff (LFB/PAS).

T cells, B cells and macrophages were detected by immunohis- tochemistry with an avidin-biotin technique using antibodies specific for CD3 (SP7; DCS Innovative Diagnostik-Systeme), CD45R/B220 (RA3-6B2; BD Biosciences) and Mac-3 (M3/ 84; BD Biosciences).

Histological sections were captured using a digital camera (DP71; Olympus Europa) mounted on a light microscope (BX51; Olympus Europa).

The percentage of demyelinated white matter was calculated using cellSens Dimension software (Olympus Europa).

Inflammatory cells were quantified at Â400 magnification using an ocular count- ing grid and are shown as cells/mm 2 .

At least eight spinal cord cross sections were taken for each analysis.


Composition of murine immune cells was analysed using the following antibodies: CD3 (145-2C11; BioLegend), CD4 (RM4-5; BioLegend), CD8 (53-6.7; BioLegend), CD45R/ B220 (RA3-6B2; BioLegend), CD11b (M1/70; BioLegend), CD11c (N418; BioLegend), F4/80 (BM8; BioLegend) and CD45 (30-F11; BioLegend).


Splenic monocyte activation/differ- entiation was determined using: CD40 (3/23; BD Bioscience), CD80 (16-10A1; BioLegend), CD86 (GL-1; BioLegend), MHCII (AF6-120.1; BioLegend), PD-L1 (MIH5; eBioscience) and LAP (TW7-16B4; BioLegend).


T-cell activation was inves- tigated using: CD25 (PC61; BioLegend), CD69 (H1.2F3; BioLegend), CD95 (Jo2; BD Bioscience) and CD44 (IM7; BioLegend).


T regulatory cell differentiation was evaluated by intracellular staining for FoxP3 (FJK-16s; eBioscience) after fixation and permeabilization using the fixation/perme- abilization kit (eBioscience).


To investigate Th1 and Th17 cell differentiation cell suspensions were stimulated with 50 ng/ml phorbol 12-myristate 13-acetate (PMA; Sigma-Aldrich) and 0.5 mg/ml ionomycin (Sigma-Aldrich) in the presence of 1 ml/ml brefeldin A (BD Bioscience) for 6 h.


Cytokine production was analysed by intracellular staining for IFN- (XMG1.2; BioLegend) and IL-17A (TC11-18H10; BD Bioscience) after fixation and permeabilization (BD Bioscience).


Fc receptors were blocked using monoclonal antibody specific for CD16/ CD32 (93; BioLegend).


Dead cells were stained with a fixable viability kit (BioLegend).


Samples were acquired on a BD LSR Fortessa (BD Bioscience).


To investigate the cytokine profile of human T cells in migration assays, cells from lower and upper chamber were stimulated with 20 ng/ml PMA and 1 mg/ml ionomycin in the presence of 1 ml/ml brefeldin A (BD Bioscience).


Dead cells were stained with LIVE/DEAD TM Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific).


CD3 (OKT3, Biolegend), CD8 (RPA-T8, BD Bioscience) and CD4 (SK3, BD Bioscience) were used for surface staining.


To assess cytokine production IL-17 (eBio64CAP17, eBioscience), IFN- (B27, BD Bioscience), GM-CSF (BVD2-21C11, BD Bioscience) and IL-4 (8D4-8, BD Bioscience) were used.


Samples were acquired on a BD TM LSRII cytometer (BD Bioscience).


All data evaluation was performed using FlowJo software (FlowJo LLC, Ashland, USA).


Production of IFN-, IL-17 and GM-CSF was measured using ELISA MAX TM Standard Set kits (BioLegend).

Absorbance was measured at 450 nm with subtraction of a 540 nm refer- ence wavelength on iMark TM microplate reader (Bio-Rad).


Thymocytes were gently dissected from wild-type mice and passed through a 70 mm cell strainer (Greiner Bio-One) and apoptosis was induced by 1 mM dexamethasone (Sigma- Aldrich) incubation overnight.

Apoptotic thymocytes were labelled with pHrodo Red, succinimidyl ester (pHrodo Red, SE; Thermo Fisher Scientific) and added to LPS pre-stimulated (50 ng/ml; overnight) splenic CD11b + cells.

After incubation of splenic CD11b + cells with apoptotic thymocytes at 37 C or on ice for 1 h phagocytosis was assessed by flow cytometry.


For the analysis of T-cell proliferation, T cells were stained with carboxyfluorescein succinimidyl ester (CFSE), for evalu- ation of differentiation or migration across the blood-brain barrier model, T cells remained unstained.

T cells were incu- bated in anti-CD3 (clone 145-2C11 for murine T cells; clone OKT3 for human T cells), or anti-CD28 (clone 37.51 for murine T cells; clone CD28.2 for human T cells) (BioLegend) pre-coated wells for 48-72 h (for murine T cells) or 96-120 h (for human T cells).

To study the effects of calcium, cholecal- ciferol, 25-(OH)-vitamin D and 1,25-(OH) 2 -vitamin D on T- cell proliferation and differentiation, T cells were preincubated with the respective components at 37 C for 1 h. Calcium chloride was dissolved in complete medium, cholecalciferol, 25-(OH)-vitamin D as well as 1,25-(OH) 2 -vitamin D were dis- solved in absolute ethanol and adjusted to contain equal etha- nol concentrations after dilution.

Monitoring of pH occurred with inoLab Õ pH Level 1 (WTW).


T cells were pre-incubated in complete Hanks' balanced salt solution (HBSS) medium (HBSS medium containing 1.3 mM CaCl 2 , 0.5 mM MgCl 2 and 1% foetal calf serum) with increas- ing calcium concentrations at 37 C for 1 h followed by stain- ing with 4 mg/ml Fluo-3 AM and 10 mg/ml Fura Red AM (Biomol) in complete HBSS (Thermo Fisher Scientific) contain- ing 0.02% Pluronic F-68 (Life Technologies) at 37 C for 30 min.

T cells were kept on ice and directly before flow cytome- try acquisition pre-heated to 37 C for 5 min.

After a 25-s baseline recording, human or mouse T cells were stimulated using 10 or 20 ng/ml ionomycin (Sigma-Aldrich), respectively.


T cells were preincubated at the indicated calcium concentrations for 1 h at 37 C followed by stimulation in anti-CD3/anti-CD28 pre-coated 6-well plates for 1-6 h (murine T cells) or for 3-20 h (human T cells) at 37 C. Total RNA was isolated using the RNeasy Õ mini kit (Qiagen) and transcribed into cDNA using the QuantiNova TM Reverse Transcription kit (Qiagen) according to the manufacturer's instructions.

Quantitative (q)PCR was per- formed using 500 nM per primer and qPCRBIO SyGreen (Nippon Genetics Europe) in a total volume of 10 ml on a QuantStudio TM 7 (Applied Biosystems).

Primers specific for IL- 2, GM-CSF, IFN- and beta-actin were purchased from Bio-Rad (for mouse) and Thermo Fisher Scientific (for human).

Quantitative PCR runs were performed at 95 C denaturating and 66 C or 68 C annealing temperature for mouse and human T cells, respectively.

Elongation was performed for 30 s and 40 cycles with subsequent melt-curve analysis.

Primer speci- ficity was validated by product size analysis using a 2% agarose gel containing GelRed (Biotium) and UV light illumination.

Detailed primer information are listed in the supplementary ma- terial (Supplementary Table 1).

Samples were analysed in dupli- cate or triplicate and considered valid when Ct 5 35 and standard deviation (SD) Ct 5 0.5.

Analysed cytokine expression was normalized to beta-actin expression loading control (ÁCt) in mice or human T cells, respectively.

ÁÁCt values were calculated in comparison to the 1.0 mM Ca 2 + condition and relative gene expression was calculated by 2 ÀddCt .


Blood-brain barrier-endothelial cells (BBB-ECs) were isolated and cultured from non-epileptic surgical human CNS material as pub- lished previously (Ifergan et al., 2006).

Written informed consent was obtained from every donor prior to surgery (CHUM re- search ethics committee; approval number BH07.001 and HD04.046).


In vitro transmigration assays were performed using a modified Boyden chamber as published previously (Ifergan et al., 2006; Larochelle et al., 2012, 2015).

In brief, human BBB-ECs were grown to confluence on gelatin-coated 3-mm pore size Boyden chambers (Collaborative Biomedical Products) in culture medium supplemented with 40% astrocyte- conditioned medium.


For the inflamed condition, TNF/IFN- (100 U/ml) was added in the upper chamber 24 h before the assay.

Boyden chambers were washed, and fresh medium was used for the transmigration assay.


Anti-CD3/anti-CD28-stimu- lated human T lymphocytes (10 6 ), which had been pre-incubated with the respective calcium concentrations were added to the upper chamber.


After 16 h, cells that had transmigrated across the BBB-ECs layer to the lower chamber were harvested, counted and analysed by flow cytometry.

Migration experiments were performed in triplicates for each donor, in all conditions.


Statistics were calculated using the software GraphPad Prism 5.01.

All in vivo and ex vivo comparisons were made to the standard vitamin D diet.

Serum concentrations of vitamin D3, serum and urine concentrations of calcium, phosphate and sodium as well as body weight, macrophage phagocytosis, ex vivo T-cell proliferation, cytokine concentrations are shown as mean AE standard error of the mean (SEM) and were analysed by the two-tailed t-test.

Quantitative PCR results, in vitro T- cell viability, pH/calcium-/chloride concentrations in medium are shown as mean AE SEM and were analysed by one-way analysis of variance (ANOVA) followed by Bonferroni's mul- tiple comparison test.

Clinical scores are depicted as mean AE SEM, composition of immune cells, white matter de- myelination and infiltration, monocyte- and T-cell activation and differentiation are shown as median and were analysed using the Mann-Whitney U-test.

Calcium flux results are pre- sented as mean AE SEM and were analysed by Kruskal-Wallis test followed by Dunn's test for multiple comparisons.

T-cell migration results are shown as mean AE SEM and were ana- lysed by Friedman test followed by Dunn's test for multiple comparisons.

Statistical analysis of the in vitro T-cell


The data that support the findings of this study are available from the corresponding author, upon reasonable request.


Mice received a diet either containing a low concentration of vitamin D3 (55 IU vitamin D3/kg), representing vitamin D deficiency, a standard (1500 IU/kg) or a high (75 000 IU/kg) dose of vitamin D3 for 15 weeks.

As indicated in Supplementary Fig. 2A, the respective diet did not influence mean body weight.


In vivo, vitamin D is hydroxylated in the liver and the kidney to its biologically active form 1,25- dihydroxy (1,25-(OH) 2 ) vitamin D3.

The half-life of 1,25- (OH) 2 vitamin D is relatively short though, so that the vita- min D status is commonly assessed by measuring 25-(OH) vitamin D (Holick, 2009).

As shown in Fig. 1A, mice in the low vitamin D group showed an average serum level below 30 nmol/l, which reflects a commonly accepted definition of vitamin D deficiency in humans (Holick, 2007).

The stand- ard group contained serum levels around 100 nmol/l, which is considered an upper normal vitamin D level in humans (Holick, 2007) and facility-housed mice (Bolton et al., 2013).

The high vitamin D diet led to serum 25-(OH) vita- min D concentrations of $250 nmol/l, a level that is com- monly achieved in patients by its continuous supplementation at high doses (Vieth, 1999; Burton et al., 2010; Smolders et al., 2010).

Mice that received the high vitamin D diet showed elevated concentrations of both total as well as ionized calcium in their serum.

Urine calcium concentrations were also substantially increased, indicating that long-term treatment with high vitamin D doses regularly caused hypercalcaemia in a predictable manner (Fig. 1B-H)


Vitamin D exerts immunomodulatory effects on cells within the innate and adaptive immune system, which widely ex- press cell surface vitamin D receptors (VDRs) (Cantorna et al., 2004).

Therefore, we examined whether the respect- ive vitamin D diet may have affected the frequency of T cells, B cells and myeloid antigen-presenting cells (APCs) in blood, lymph node and spleen.

As indicated in Supplementary Fig. 3, high vitamin D was associated with an increase in frequency of T cells and fewer B cells in the blood.

Moreover, in the spleen, these mice contained an elevated frequency of CD11c + dendritic cells and F4/ 80 + macrophages.


EAE was induced after chronic vitamin D supplementa- tion.

All three treatment groups developed EAE around Day 12 (Fig. 2A).

Mice that received the stand- ard dose of vitamin D developed the lowest scores, as ex- pected based on earlier EAE studies showing that short- term oral vitamin D administration ameliorated EAE and impaired activation and CNS migration of monocytes (Nashold et al., 2000) and T cells (Mayne et al., 2011).


Surprisingly, mice supplemented with high vitamin D dose manifested a more severe EAE course.

Mice were main- tained on their respective diet throughout the entire disease course.

Recognizing nutrition as a potential confounder, we monitored weights daily.

While low and high vitamin D groups had modestly higher mean body weights within days after immunization, there were no significant differ- ences in body weights in any groups throughout the disease course (Supplementary Fig. 2B).


The unexpected clinical observation of an EAE exacerba- tion in the group of mice containing high vitamin D serum levels was further corroborated by histological analyses, revealing a significantly increased inflammatory infiltration of the CNS (Fig. 2B).

An abundance of activated CNS infiltrating myeloid cells as well as an elevated number of CNS T cells was observed in the high dose vitamin D group (Fig. 2C-E).

Enhanced cellular infiltration was associated with an increase in the extent of CNS demyelination (Fig. 2F).


CNS T cells were isolated and evaluated for their dif- ferentiation.

As indicated in Fig. 2G, CNS T cells from mice with high vitamin D levels contained a significantly higher frequency of IFN- or IL-17 producing Th1- and Th17 cells, respectively.

In contrast, the frequency of FoxP3 + regulatory T cells (Treg) within the CNS was slightly lower in the high vitamin D group (Fig. 2H).


Taken to- gether, the high dose vitamin D diet was associated with higher absolute numbers of myeloid cells and T cells and pro-inflammatory differentiation of these cells.


In light of the increased inflammatory CNS infiltration we analysed whether continuously high levels of vitamin D had Hypercalcaemia by vitamin D exacerbates EAE BRAIN 2019: 142; 2737-2755 | 2741 Downloaded from https://academic.oup.com/brain/article/142/9/2737/5532100 by Institut Armand-Frappier user on 16 May 2024 promoted peripheral immune cell activation and differenti- ation prior to CNS transmigration.


As shown in Fig. 3A, myeloid APC from mice in the vitamin D high group indeed showed an enhanced surface expression of MHC class II and co-stimulatory CD40, CD80 and CD86.


In contrast, expression of PD-L1, an inhibitory costimulatory molecule (Salama et al., 2003), or latency-associated pep- tide (LAP), a surface molecule indicative of a Treg-fostering TGF-beta production (Miyazono et al., 1991), was un- affected by the high vitamin D diet.


As a prerequirement for presentation to T cells, larger antigens must first be phagocytosed and processed by the APC.


As indicated in Fig. 3B, in vivo vitamin D treatment dose-dependently increased the phagocytic capacity of mye- loid macrophages.


While this is likely of benefit in clearance of infections (Djukic et al., 2015), enhanced uptake of auto-antigen in contrast enlarges the basis to generate an auto-reactive adaptive immune response (Kinzel et al., 2016).


In conjunction with the elevated frequency of CD11c + dendritic cells and highly differentiated F4/80 + macrophages in vitamin D- treated naïve mice (Supplementary Fig. 3) these data thus suggest that high dose vitamin D supplementation is associated with matur- ation of myeloid APC, an increased surface expression of the molecular machinery participating in phagocytosis and antigen presentation.


Standard and high vitamin D3 treatments were associated with a significant increase in expression of the early acti- vation marker CD69 on T cells.

There were also dose-de- pendent increases in the frequencies of activated CD25 + and antigen-experienced CD44 hi memory T cells (Baaten et al., 2012) (Fig. 4A).


Of interest, standard and high vita- min D supplementation was associated by an increase in Treg (Fig. 4B).


When T cells were restimulated in vitro by anti-CD3/anti-CD28, however, in vivo high dose vitamin D-exposed T cells proliferated at a significantly higher rate as assessed by dilution of an intracellular dye (Fig. 4C) and preferentially differentiated into IFN- pro- ducing Th1 and IL-17 releasing Th17 cells (Fig. 4D and E).


The possibility that pro-inflammatory Th1 and Th17 dif- ferentiation of high vitamin D was due to a direct effect on T cells, or was a secondary effect resulting from enhanced APC maturation was investigated.

Here, we used a co-cul- ture system, in which naïve T cells were activated by mye- loid APC.

Either cell type was isolated from mice fed with low, standard or high vitamin D doses.


Based on the substantial phenotypic alterations of CD11b + myeloid cells, we first focused on a possible APC-driven effect.

As indicated in Fig. 5A, myeloid APC continuously exposed to high vitamin D levels triggered a slightly higher prolifer- ation of myelin-specific T cells.


Yet, in vivo exposure of T cells to vitamin D exerted the greater contribution to enhanced T-cell proliferation; T cells isolated from mice treated with low or high vitamin D doses always prolifer- ated at a significantly higher rate independent of whether the activating myeloid APC had been treated with low, standard or high vitamin D (Fig. 5B).


Most strikingly, naïve myelin-specific T cells, which had been exposed to high vitamin D levels in vivo consistently differentiated into Th1 and Th17 cells, largely independent of the respect- ive APC origin (Fig. 5C and D); conversely, low, but even more so high vitamin D effectively prevented development of Treg ex vivo (Fig. 5E).


Of note, the standard vitamin D diet generated T cells with the greatest propensity to differ- entiate into Treg cells when activated ex vivo, which is in line with a reported fostering effect of moderate vitamin D levels on the frequency and function Treg in mice (Korf et al., 2012) and humans (Barrat et al., 2002).


Next, to confirm that high 25-(OH) vitamin D levels influenced T- cell activation and differentiation directly in an antigen- and APC-independent manner, we stimulated CD4 + or CD8 + T cells purified from naïve mice fed with the low, medium and high vitamin D diet by anti-CD3/anti-CD28 directly.


Parallel with our findings in EAE-diseased mice, high-dose vitamin D treatment accelerated proliferation of both CD4 + and CD8 + T cells (Fig. 5F and G).


In addition, T cells from high dose vitamin D-treated mice differentiated in a pro-inflammatory manner, when activated ex vivo (Supplementary Fig. 4).


Based on these findings, next, we assessed the direct effect of vitamin D and its metabolites on both human and murine T cells in vitro.

Purified T cells were pre-incubated with cholecalciferol, 25-(OH)-vitamin D or 1,25-(OH) 2 - vitamin D at increasing concentrations.

Most importantly, these concentrations reflected both the serum ranges mea- sured in our EAE study as well as low, physiological, and supra-physiological levels in humans.


None of the vitamin D concentrations affected viability of human or murine T cells in culture (Supplementary Fig. 5A-F).

As indicated in Fig. 6A-F, 25-(OH)-vitamin D or 1,25-(OH) 2 -vitamin D clearly inhibited proliferation of both human and murine CD4 + and CD8 + T cells in a dose-dependent manner, while non-hydroxylated cholecalciferol only exerted this effect on human T cells.


These results confirmed a direct regulatory effect of vitamin D itself on T cells (Mayne et al., 2011; Peelen et al., 2011) and thus failed to explain the enhanced proliferation and pro-inflammatory differen- tiation of T cells observed in high dose vitamin D-treated mice.


In search of an alternative explanation, we next investi- gated a possible T-cell excitatory effect of calcium (Quintana et al., 2011; Monaco et al., 2016) in our model.

Purified human and murine T cells were exposed to various calcium concentrations ranging from 1 to 3 mM (Fig. 7A-H).

Importantly, in these in vitro assays we extended the range to include lower concentrations of cal- cium, having in mind that in the serum of our vitamin D- treated mice a substantial proportion is bound to protein (Fig. 1B, C and Supplementary Fig. 6A), which may reduce its direct availability for T cells proportionally.

As shown in Fig. 7A and B, calcium dose-dependently accelerated pro- liferation of both human and murine CD4 + and CD8 + T- cells in this setting, while chloride levels, pH and T-cell viability remained unaffected (Supplementary Fig. 6B-E).

Further dissecting this observation, we monitored the cellu- lar calcium influx upon T-cell activation (Gwack et al., 2007).

To account for a protein-reduced medium in these assays we used a lower range of total calcium concentra- tions (Supplementary Fig. 6F) and checked again that chlor- ide levels and pH remained unaffected (Supplementary Fig. 6G and H).

As indicated in Fig. 7C and D, raising extra- cellular calcium to concentrations again equivalent to the serum levels of ionized calcium in our vitamin D fed mice caused a significant increase in the mean calcium influx, triggering an upregulation of pro-inflammatory gene prod- ucts (Fig. 7E and F).

Lastly, we corroborated that this direct T-cell stimulating effect of calcium also occurred in vivo.

For this purpose, we repetitively and continuously


Geographical latitude correlates with multiple sclerosis in- cidence (Acheson et al., 1960) which highlights the influ- ence of environmental factors in multiple sclerosis (Ascherio and Munger, 2007).

Lack of exposure to sun- light, UV radiation and hereby relatively low levels of vita- min D in the context of its emerging immunoregulatory properties provides one attractive explanation for this cor- relation (Nielsen et al., 2017); the central question remain- ing though is whether lack of vitamin D is causal in triggering multiple sclerosis activity or an epiphenomenon of insufficient sun light exposure as the true risk factor (Schwarz et al., 2012).

A direct effect of vitamin D on multiple sclerosis activity is yet the conceptual requirement for all current efforts to therapeutically raise its level in affected patients.

Empiric vitamin D supplementation stu- dies thus far have provided conflicting results (Stein et al., 2011; Loken-Amsrud et al., 2012).

For example, adding vitamin D3 to interferon treatment reduced MRI activity in a small trial with relapsing-remitting multiple sclerosis patients (Soilu-Hanninen et al., 2012), which was recently confirmed by a larger phase II study (Hupperts et al., 2017).


Unfortunately, the conclusions from these studies are limited as both interferon-beta (IFNb) and vitamin D interact in modulating multiple sclerosis disease activity, and data indicate that sufficient vitamin D is a prerequisite for the benefit of IFNb (Stewart et al., 2012).

While available data indicate that moderate vitamin D supplemen- tation is safe in multiple sclerosis (Sotirchos et al., 2016), results of ongoing larger placebo-controlled trials are needed to clarify whether therapeutic vitamin D supplemen- tation is beneficial in multiple sclerosis independent of con- comitant disease modifying therapy.


Our results suggest that modest vitamin D supplementa- tion may have a beneficial effect in EAE, while those data were not significant.

We report here, to our knowledge for the first time, that continuous supplementation with high doses of vitamin D yet exerted a highly significant para- doxical effect, promoting exacerbation of clinical and histo- logical EAE.

This outcome was underpinned by an accentuated phenotype and function of myeloid APC as well as an unleashed development of pro-inflammatory T cells upon high dose vitamin D treatment.

Further, high- dose vitamin D similarly accelerated activation and differ- entiation of both myeloid APC and T cells in unimmunized healthy mice (Fig. 5F, G and Supplementary Fig. 7), indi- cating that the high vitamin D dose exerted a broad immune cell activating effect independent of an inflamma- tory context.


At first glance, these findings appear to con- flict with several other experimental studies, which mainly reported a clinical benefit of vitamin D treatment in EAE, also at higher doses (Lemire and Archer, 1991; Cantorna et al., 1996; Nashold et al., 2000); however, all of these studies evaluated short-term vitamin D supplementation.

In most of these studies, hydroxylated forms of vitamin D were investigated in a brief intervention regimen.

Most likely as a result, none of these studies reported develop- ment of hypercalcaemia.

Elevated serum calcium was, how- ever, observed in another study continuously exposing mice to high doses of vitamin D (Spach and Hayes, 2005), again suggesting that it may develop only after an extended period of exposure.


The strength of our study is that we supplemented vitamin D for several months before assess- ing EAE susceptibility, and that we fed cholecalciferol, the metabolite supplemented in humans.

As a result, we mea- sured serum levels of 25-(OH) vitamin D, again the mol- ecule most commonly assessed in humans, reflective of patients with multiple sclerosis considered vitamin D-defi- cient, with physiological or high vitamin D levels


Binding of vitamin D to immune cells and subsequent VDR signalling regulates pro-inflammatory immune func- tions (Peelen et al., 2011) and is likely of benefit in sup- pression of CNS autoimmune disease (Meehan and DeLuca, 2002; Xie et al., 2017).

In line with these studies, our in vitro results confirm a direct beneficial effect of vita- min D and its metabolites on T cells (Peelen et al., 2011), inhibiting their activation and pro-inflammatory differenti- ation.

Of note, the extent of this effect was consistently greater on CD8 + than on CD4 + T cells, following the relative expression levels of the VDR on these cells (Veldman et al., 2000).

Interestingly, B cells can only react to vitamin D after initial activation and subsequent upregulation of the VDR, as their constitutive expression is relatively low (Provvedini et al., 1983, 1986).

Nevertheless, 1,25(OH) 2 D 3 has been shown to reduce B-cell prolifer- ation, plasma and memory cell differentiation and induced apoptosis in proliferating B cells (Chen et al., 2007).


These findings suggest that the direct effect of vitamin D on both human and murine lymphocytes is indeed of anti- inflammatory nature and most likely beneficial in an auto- immune setting.


Our results indicate that in contrast, a rise in the serum calcium exerts the opposite effect on T cells, which can ap- parently override any clinical benefit of vitamin D in EAE.

This is in line with the earlier finding that adding the cal- cium-lowering hormone calcitonin additively augmented the therapeutic benefit of a vitamin D in EAE (Becklund et al., 2009).

Calcium acts as a second messenger promoting cell cycle progression in many cell types, including lymphocytes (Feske, 2007).

T-cell receptor signalling raises intracellular calcium at first by its release from the endoplasmatic reticu- lum, and to the greater extent by subsequent extracellular calcium influx through plasma membrane calcium channels (Kuno and Gardner, 1987; Lewis, 2001).

Only the latter is capable of raising intracellular and nuclear calcium levels over an extended period of time, which is required to pro- mote activation, proliferation and differentiation of immune cells (Dolmetsch et al., 1998; Vig and Kinet, 2009), includ- ing clonal expansion of T cells (Vaeth et al., 2017).


This is precisely the scenario and the sequence of events which we identified to underlie deterioration of EAE severity in our study.

Modelling hypercalcaemia at the levels observed upon continuous high dose vitamin D treatment in vivo acti- vated T cells independent of vitamin D. Mechanistically, an elevated level of calcium triggered its increased influx into T cells upon activation, which led to an upregulation of pro- inflammatory gene products.

These initial events were fol- lowed by an unleashed proliferation and encephalitogenic differentiation of both human and murine T cells, corrobor- ating a causal sequence of high dose vitamin D treatment, secondary hypercalcaemia and a promoted development of disease-driving encephalitogenic T cells.

While there is cur- rently no molecule to selectively interfere with the calcium influx into immune cells in vivo, genetically determined in- ability of these calcium channels to function in T cells com- pletely blocked EAE by preventing development of myelin- reactive Th1 and Th17 cells (Ma et al., 2010).

Along the same lines, therapeutic blockade of calcium channels by nimodipine was recently reported to suppress EAE (Schampel et al., 2017).

This clinical benefit was primarily attributed to restored remyelination, but furthermore, may relate to attenuated T-cell activation.

In conjunction, these findings indicate that worsening of EAE in our high vitamin D group indeed occurred as a consequence of raising the mean calcium level.

In greater context, these data implicate that the clinically desirable effect of modest vitamin supple- mentation may be reflective of immune-regulatory VDR sig- nalling, while exacerbation of T cell-mediated CNS autoimmunity at excessive vitamin D doses is primarily attributed to raising the mean calcium level.


Hypercalcaemia in its extent comparable to the levels associated with deterioration of EAE commonly occurs in humans supplemented with high doses of vitamin D (Malihi et al., 2016).

In conjunction with these observations, our novel findings highlight excessive vitamin D supplementation and resulting hypercalcaemia as novel risk factors promot- ing worsening of CNS demyelinating disease.

Our data cau- tion that in light of the currently limited information on a direct beneficial effect of vitamin D in multiple sclerosis, patients with multiple sclerosis may be at danger of experi- encing untoward immunological and/or clinical effects when vitamin D is supplemented excessively.


We read the recent paper of Ha¨usler et al. ( 2019) with great interest.

The authors report observations in the experimental autoimmune encephalomyelitis (EAE) model suggesting that vitamin D3-induced hypercalcaemia is detrimental for the disease course of multiple sclerosis.

The main sign of vitamin D toxicity is hypercalcaemia, which can lead to loss of kidney function and cardiovascular complications, among others [1].

Ha¨usler et al. show that high calcium levels exacerbate immunological processes potentially harmful for neuroinflammation of multiple sclerosis.

In their experiments, 10 weeks of high-dose vitamin D3 in C57BL/6 mice (n = 8) induced 25(OH)D levels exceeding 200 nmol/l, a rise of circulating calcium levels, and a steep increase in urine calcium levels [2].

We performed several supplementation studies using high-dose vitamin D3 supplements in patients with multiple sclerosis, and did not observe these dramatic effects on markers of calcium metabolism.


A safety study of 12 weeks of 500 mg/d (20 000 IU/d) vitamin D3 supplements in 15 interferon beta-treated participants with relapsing remitting multiple sclerosis (RRMS) showed no cases of hypercalciuria, defined as a spot urine calcium/creatinine ratio exceeding 1.0 mM/mM [3].

Additionally, no cases were observed of hypercalcaemia, defined as serum calcium levels exceeding 2.6 mmol/l.

At group level, serum calcium levels remained stable.

Serum 25(OH)D levels were elevated to a median level of 380 nmol/l.

One relapse of multiple sclerosis occurred at Week 7, another at Week 19 during the safety follow-up.

No increases in CD4 + T cells producing interferon gamma (IFN-γ) or interleukin 17 (IL-17) were noted.


In the SOLAR trial, 48 weeks of 350 mg/d (14 000 IU/d) vitamin D3 supplements in n = 113 versus placebo in n = 116 interferon beta-treated participants with RRMS did not show any cases of hypercalcaemia using the same definitions [4].

There were two cases of mild-to-moderate hypercalciuria in the vitamin D3, and three in the placebo group.

Serum 25(OH)D levels were elevated to a median level of 215 nmol/l.

There was no difference in proportion of participants free of disease activity between the treatment arms; secondary MRI endpoints suggested benefit in the vitamin D3 arm.

In a subgroup of Dutch participants, no increases in CD4 + T cells producing IFN-γ, IL-17 or granulocyte macrophage colony stimulating factor (GM-CSF) were noted [5].


In a 16-week study of 100 mg/d (4 000 IU/d) vitamin D3 supplements in 25 first line disease-modifying drug-treated participants with RRMS versus placebo (n = 23), no cases of hypercalcaemia were observed, using the same definitions [6].

At the Week 8 visit, there were five cases of hypercalciuria, three in the placebo and two in the vitamin D3 arm, which all resolved spontaneously.

Serum 25(OH)D levels were elevated to a median level of 139.9 nmol/l.

Two relapses were recorded, one in the vitamin D3 and one in the placebo arm.

No increases in CD4 + T cells producing IFN-γ, IL-17, or GM-CSF were noted [7].


The effects of increased 25(OH)D levels on serum and urine calcium levels in inbred mouse strains suffering from EAE cannot be extrapolated to people suffering from multiple sclerosis.

However, the data of Ha¨usler et al. stress the importance of monitoring calcium metabolism carefully in clinical studies on high doses of vitamin D3 in multiple sclerosis [8].

High-dose vitamin D3 supplements without hypercalcaemia were not associated with adverse multiple sclerosis outcomes, or with a more pro-inflammatory composition of the T cells.

These observations are supported by several other controlled studies on moderate to high-dose vitamin D3 supplementation in multiple sclerosis [9][10][11][12][13][14].

The question whether supplementing such high doses of vitamin D3 is of any additional benefit on relevant multiple sclerosis endpoints when compared to moderate doses should become clear from controlled studies comparing these doses or meta-analyses of clinical trials.


Hereby we would like to reply to the comments by Smolders et al. ( 2019) regarding our recent publication describing a clinical deterioration in a murine model of multiple sclerosis upon high-dose vitamin D supplementation, which is mediated by a T cell-stimulatory effect of secondary hypercalcaemia [1].

Smolders et al. highlight that several high-dose vitamin D supplementation studies in multiple sclerosis patients reaching 25(OH)D median levels of up to 380 nmol/l reported no hypercalcaemia [2][3] and only single cases of hypercalciuria [4] occurring in both the treatment and placebo groups.

Moreover, the authors described no development of pro-inflammatory T cells after high-dose vitamin D supplementation, concluding that hypercalcaemia rather than high-dose vitamin D3 supplements could exacerbate multiple sclerosis.


We agree with this suggestion, observing that a moderate dose of vitamin D suppressed experimental autoimmune encephalomyelitis (EAE) and that direct in vitro exposure of murine or human T cells to vitamin D and its metabolites even at supra-physiological doses inhibited proliferation and pro-inflammatory differentiation.

By contrast, directly exposing murine, but also human CD4+ and CD8+ T cells to hypercalcaemic concentrations caused an increased susceptibility to activation, an upregulation of pro-inflammatory gene products as well as an enhanced capacity of activated T cells to transmigrate across a blood–brain barrier model.

Moreover, raising calcium concentrations directly in vivo resulted in increased expression of activation markers on CD4+ and CD8+ T cells.


We want to emphasize that our investigations hereby support that vitamin D itself exerts a favourable effect in inflammatory CNS demyelinating disease; furthermore, we fully agree that our experimental data by no means can be used to extrapolate how regularly and/or persistently hypercalcaemia occurs upon high-dose vitamin D supplementation in patients with multiple sclerosis; to date it indeed has only been reported in a few cases on high dose vitamin D therapy, especially when combined with calcium intake [5][6][7].

Yet we believe that our mechanistic observations caution that an uncritical and continuous supplementation with very high doses of vitamin D as propagated by few individuals in the field may not be advisable, especially when possible effects on the calcium metabolism are not regularly monitored.

In this situation, the undesirable effects of hypercalcaemia, including the newly reported activation of potentially pathogenic T cells, may indeed occur more frequently and outweigh any possible benefit of vitamin D itself.


We believe that the comments by Smolders et al. thus adequately contextualize our experimental data, and that we can jointly conclude on the note that moderation and monitoring may be advisable in vitamin D supplementation of multiple sclerosis.


Participants in the Multiethnic Cohort Study were re- cruited between 1993 and 1996 through targeted mailings to men and women aged 45-74 years.

A total of 215,251 men and women completed a self-administered baseline questionnaire that obtained information on medical history, family cancer history, diet, medication usage, physical ac- tivity, smoking history, alcohol intake, and women's repro- ductive history, including menopausal status and hormone use.

A description of the methods used to create the cohort and the characteristics of cohort members has been pub- lished elsewhere (19).

The proposal for this work was ap- proved by the institutional review boards of the University of Southern California and the University of Hawai'i.

Informed consent was obtained in writing from cohort par- ticipants, as per the protocol.


A total of 103,893 female African-American, Japanese- American, Native Hawai'ian, Latina, and non-Latina White cohort members with no history of breast, ovarian, or endo- metrial cancer were eligible for this study.

Of these, 95,704 women with a mean age of 59.7 years (10th-90th percentile range, 47.0-71.0) had valid nonmissing data for the vari- ables of interest and were included in the final analysis (table 1).

Only data from the baseline questionnaire were used in the current analysis.


A woman was considered postmenopausal if her men- strual periods had stopped naturally or if she had undergone a hysterectomy or bilateral oophorectomy.

Women in the second category were censored in this analysis, as were pre- menopausal women.

For 1,452 women who were missing data on age at menopause but for whom we had data on when they began using hormone therapy, the age at initiation of hormone therapy was assigned as the age of menopause.


Age at menopause was recorded in the baseline question- naire in four categories: <45, 45-49, 50-54, and 55 years.

Women who were older at baseline than the maximum age of the selected category were assigned an event age at the midpoint of the category (43, 47, 52, or 57 years).

If a subject's age at baseline was within the category she se- lected for her age at natural menopause, her event age was calculated as the midpoint between the start of the category and her age at baseline.

Premenopausal subjects were as- signed a censoring age in a parallel manner.

For example, a 53-year-old premenopausal woman was censored at age 51.5 years, the midpoint between her age at menopause and the start of the corresponding age-at-menopause category.


Categories of age at hysterectomy or bilateral oophorec- tomy were <45, 45-49, and 50 years.

Subjects reporting menopause by surgery in one of the first two categories (<45 years or 45-49 years) were assigned a censoring age in a manner parallel to the manner in which naturally men- opausal subjects were assigned an event age.

Women with surgical menopause whose age at baseline was older than the highest age of the self-reported age-at-surgery category were assigned a censoring age at the midpoint of the self- reported age-at-surgery category (43 years or 47 years).

If a subject's age at baseline fell within the category she se- lected for her age at surgery, the censoring age was calcu- lated as the midpoint between the start of the category and her baseline age.

Subjects reporting menopause by surgery in the highest category (50 years) were treated in a differ- ent manner, because the age at natural menopause had one additional category on the upper end (55 years).

Subjects between 50 and 54 years of age at baseline were assigned a censoring age at the midpoint between their baseline age and 50 years.

Subjects aged 55-57 years at baseline were censored at the midpoint between their baseline age and 55 years, and those older than 57 years at baseline were censored at age 57 years.


In addition to race/ethnicity, we considered the following factors, on which data were collected at baseline, as poten- tial predictors of the timing of natural menopause: smoking history, age at menarche, age at first full-term pregnancy, parity, years of oral contraceptive use, and body mass index (weight (kg)/height (m) 2 ).

Table 1 shows the categories used for each of these factors.

Smoking history was defined by a six-level variable that separated women whose smoking might have been temporally relevant to menopause (never smoker, smoker who started smoking after age 45 years, smoker who quit before age 45 years and smoked 10 cig- arettes per day, smoker who quit before age 45 years and smoked >10 cigarettes per day, current smoker at age 45 years who smoked 10 cigarettes per day, and current smoker at age 45 years who smoked >10 cigarettes per day).

Body mass index was categorized according to World Health Organi- zation guidelines (<20, 20-24.9, 25-29.9, or 30) (20).


We used univariable and multivariable Cox proportional hazards regression with age as the time metric (21) to assess the association (hazard ratio) between exposure and out- come variables.

Subjects were considered to have entered the study at birth and remained under follow-up until they completed the baseline questionnaire (when they joined the Multiethnic Cohort Study) or until one of the following events occurred: natural menopause (event) or surgery re- sulting in the end of menses, including hysterectomy and/or bilateral oophorectomy (censored observation).

Thus, women who were premenopausal at baseline were censored at the A series of univariable analyses were performed in which a model with each single variable of interest was tested by likelihood ratio test against a model that fitted only an in- tercept term.

Variables showing statistically significant as- sociations with timing of natural menopause in univariable analyses were subsequently tested for independent associa- tions in a multivariable model.

We fitted a series of multi- variable failure-time models in which a woman failed at the time of natural menopause and which included both race/ ethnicity and smoking to determine the factors associated with the relative timing of natural menopause.

A forward stepwise regression approach was used, with variables enter- ing the model when at least one of the categories had a p value less than 0.01.

Once a full model was identified, a backward stepwise regression approach was used, with variables being excluded when no category had a p value less than 0.01.

Trend tests for ordinal variables were performed by fitting as a single variable the ordinal categories of increasing expo- sure.

A test for interaction with race/ethnicity was performed on each covariate retained in the final model.

All statistical significance levels (p values) quoted are two-sided.

An alpha level of 0.05 was used as the threshold for statistical signif- icance, unless otherwise explicitly stated.


The study population included a substantial proportion of Japanese-American (27.8 percent), non-Latina White (25.4 percent), Latina (20.8 percent), and African-American (18.8 percent) women (table 1).

In addition, 7.2 percent were Native Hawai'ians.

Of the Latinas, 48.5 percent had been born outside of the United States.

A chi-squared test for the difference in the proportions of subjects by racial/ethnic group for each variable shown in table 1 was statistically significant (all p's 0.01).


In characterizing the study pop- ulation, African Americans tended to be somewhat heavier and to have earlier first full-term pregnancies and were more likely to have undergone surgical menopause (hysterectomy and/or bilateral oophorectomy (43.1 percent)) than women in any of the other racial/ethnic groups.

In table 1, partic- ipants in the category of surgical menopause by bilateral oophorectomy may also have had a hysterectomy, whereas participants categorized as having undergone surgical men- opause by hysterectomy had only ever had a hysterectomy.


Native Hawai'ians were the youngest of the racial/ethnic groups and were relatively overweight.

Japanese Americans were leaner, were less likely to smoke (as were the non-US- born Latinas), and had a later age at first full-term pregnancy than women in other racial/ethnic groups.

A greater propor- tion of non-Latina Whites were nulliparous than women in other racial/ethnic groups.

Non-US-born Latinas had later ages at menarche than US-born Latinas.


In the univariable analyses, race/ethnicity and smoking were significantly associated with the timing of natural menopause (data not shown).

Thus, in testing of additional variables, we retained race/ethnicity and smoking in the models.

Age at menarche, age at first full-term pregnancy, parity, years of oral contraceptive use, and body mass index were significantly associated with relative timing of natural menopause in univariable analyses with race/ethnicity and smoking forced into the model.

Of these factors, age at menarche, parity, and body mass index were significantly independently associated with relative timing of natural menopause in the multivariable model, in addition to race/ ethnicity and smoking (table 2).


In table 2, the independent effect of race/ethnicity in the timing of natural menopause in the multivariable model is evident.

Latinas, particularly those not born in the United States, experienced significantly earlier menopause than did non-Latina Whites (non-US-born Latinas: hazard ratio (HR) ¼ 1.25, 95 percent confidence interval (CI): 1.21, 1.30; US-born Latinas: HR ¼ 1.10, 95 percent CI: 1.07, 1.14).

Native Hawai'ians showed a borderline-significant effect that pointed in the same direction as the effect for Latinas (HR ¼ 1.05, 95 percent CI: 1.01, 1.09).

African Americans did not differ significantly from non-Latina Whites (HR ¼ 0.99, 95 percent CI: 0.96, 1.02).

Japanese Americans expe- rienced later menopause than non-Latina Whites (HR ¼ 0.93, 95 percent CI: 0.90, 0.95).

Race/ethnicity-specific hazard ra- tios were obtained from a series of models in which race and smoking were forced in and into which each covariate associ- ated with the timing of natural menopause was added in- dividually.

A comparison of these models showed no alteration in the race/ethnicity-specific hazard ratios (data not shown).


Age at natural menopause in the developed world is ap- proximately normally distributed, ranging between 40 years and 58 years, with an approximate mean of 51.4 years (22).

This broad range may be due to real differences in age at natural menopause, driven by variation in an incom- pletely defined set of predictors.

It may also be attributed to methodological issues, including differing or problematic methods of classification of menopausal status, use of con- venience samples such as hospital patients, potentially in- accurate recall in retrospective assessment of age at event and covariate information, inconsistent treatment of hormone therapy users, lack of data on demographic and physiologic covariates, and paucity of data on diverse pop- ulations (see reviews by the World Health Organization (23) and Crawford (24)).


In the current study, we investigated a host of lifestyle and reproductive variables that may influ- ence the timing of natural menopause in the large, population- based Multiethnic Cohort Study cohort.

In this racially/ ethnically diverse study of over 90,000 women, Japanese- American race/ethnicity was independently associated with relatively late natural menopause and Latinas were found to experience relatively early natural menopause, with those born in the United States experiencing the event later than those born outside the United States.

Adjustment for other factors did not significantly alter the magnitude of these racial/ethnic effects.


Most previous studies that assessed predictors of the tim- ing of natural menopause did not address whether the timing of natural menopause differed by race/ethnicity, because of the predominance of European ancestry in the study popu- lations (6, 25-31).

The findings of one prospective study (13) and three cross-sectional studies (14-16) suggested that African-American women experienced natural menopause earlier than non-Latina Whites; Gold et al. ( 17) reported that Japanese Americans experienced menopause later than non- Latina Whites.

None of these findings were conclusive.


The independent racial/ethnic effect reported in this study does not discount the hypothesis that age at natural meno- pause is a heritable trait.

Torgerson et al. ( 8) reported an association between age at natural menopause and maternal age at natural menopause in a study of 551 women.

Inves- tigators have reported heritability estimates for age at natural menopause that have ranged from 31 percent to 63 percent (11, 12, 32, 33).

Genome-wide linkage studies with age at natural menopause as a continuous quantitative phenotype have identified several loci with strong signals (34, 35).

Other studies have suggested associations with single nucleotide polymorphisms in genes in several pathways (36-41).


Of all environmental factors studied previously, smoking has been most consistently associated with the timing of natural menopause (17, 42-48).

We have reported a dose- response relation between timing and amount of smoking and age at natural menopause that is consistent with evi- dence from a quantitative review (49).

The mechanism by which smoking affects the timing of natural menopause is not fully understood, and it is likely to involve more than one pathway (50-53).


Reproductive factors, particularly those hypothesized to influence ovulation or follicle attrition, are somewhat contro- versial with respect to timing of natural menopause.

The di- rection of our results regarding age at menarche (54) and parity (13, 25, 27, 48) is consistent with previous reports.

In our data, it appears that women with a low body mass index (body mass index <20) have an earlier age at natural meno- pause than heavier women.

In the postmenopausal period, women with a high body mass index have higher circulating levels of estrogen than leaner women through the increased aromatization of androstenedione that occurs in body fat (55).

It is possible, in women transitioning through menopause (i.e., perimenopausal women), that some additional adipose- tissue-derived estrogen may support the continuation of menstrual cycles in heavier women relative to leaner women.


The current study had several strengths.

The multiethnic design enabled us to attempt to address whether the timing of natural menopause differed by racial/ethnic group.

Ex- tensive information from the baseline questionnaire offered us the opportunity to assess racial/ethnic variation in the timing of natural menopause while controlling for a number of potentially confounding factors.

Use of a failure-time modeling approach enabled us to avoid excluding a large proportion of subjects.


However, this analysis was potentially limited by several factors.

In particular, this is a cross-sectional data set and it may contain errors in recall.

For example, we might predict that increased error in recall would be associated with in- creasing age or decreasing socioeconomic status.

To assess this quantitatively, we conducted an analysis limited to women who were less than 60 years of age at baseline.

We also tested the addition of an attained education variable (high school or less, some college/vocational school, college graduation or higher) as a surrogate for socioeconomic sta- tus.

Finally, we limited the analysis to women with an edu- cation in the higher two categories.

With no method did any of the race/ethnicity-specific hazard ratios change by more than 10 percent.

These results argue against differential re- call by age and socioeconomic status.


Another limitation stems from the fact that the variable for age at natural menopause was categorical, which pre- vents the easy translation of the hazard ratios into a differ- ence in years or months.

However, to provide an idea of what a hazard ratio means in terms of months, we used a method published by Krailo et al. ( 56).

Assuming a median age at natural menopause of 50 years, a hazard ratio of 1.25, corresponding to the largest multivariate race/ethnicity- specific hazard ratio reported herein, which was specific to the non-US-born Latinas, would translate into a difference of 0.72 years or 8.64 months.


In addition, there was a small group of women (n ¼ 1,452; 1.5 percent of the total) who were missing data on age at menopause but for whom we had data on when they began using hormone therapy.

For these women, we defined age at menopause as the age at which they reported starting the use of hormone therapy.

By definition, these women will tend to have been assigned a menopausal age lower than their true age at menopause.

This would mean that groups with higher proportions of such women would appear to have had an earlier meno- pause.

We tested whether our coding was biasing our results in several ways, including 1) entering an indicator variable (1 ¼ age at menopause assigned as age at first use of hor- mone therapy, 0 ¼ age at menopause known) in the final multivariable model, 2) censoring the women with an age at menopause assigned as age at first use of hormone therapy at the age at first use of hormone therapy, and 3) excluding all of the women with an age at menopause assigned as age at first use of hormone therapy.

There was no significant change in the race/ethnicity-specific hazard ratios, indicat- ing that our coding did not produce material bias.


The categorical nature of these data also posed a problem in choosing a method for assignment of censoring ages.

We tested methods extensively.

For example, for women older than 55 years at baseline who reported an age at surgical menopause of 50 years or older, we tested several methods, including one in which we assigned a censoring age based on the relative distribution of the timing of natural meno- pause by race/ethnicity.

The estimates for the race/ethnicity- specific hazard ratios did not change significantly from those shown for any of these different methods.


Another possible limitation of our data was our measure of body mass index.

Since we did not have access to body mass index as a time-dependent variable, we relied on body mass index at baseline as an approximation of relevant body mass index.

We find no conclusive prospective evidence in the literature for an independent effect of menopause on body mass index.

In fact, we consider this an interesting future research question.


However, there is evidence that weight in women increases with age (55).

Thus, the partic- ipants who enrolled at older ages (postmenopausal women) will have tended to have higher body mass indices than they had at the age of menopause.

For older women, body mass indices will have been overestimated in the model.

Measure- ment bias would be possible if, for example, older women, with overestimated body mass indices, also tended to report later menopause than younger women.

These women would then appear to have a higher body mass index and later menopause.

However, in a sensitivity analysis excluding women over age 60 years, we found no evidence of bias in race-specific estimates by age.


Use of the failure-time modeling approach to assess predictors of the timing of menopause in this large, multi- ethnic sample provided us with ample statistical power to detect small differences in the hazard ratios for timing of natural menopause between strata.

We were able to show a significant racial/ethnic difference in the timing of natu- ral menopause that was independent of adjustment for po- tential confounders, and we have provided confirmatory evidence for factors hypothesized to be associated with the timing of natural menopause that had heretofore re- mained controversial in the literature.

These findings sup- port the hypothesis that the timing of natural menopause is driven by a combination of genetic, reproductive, and life- style factors.


In the article recently published by Henderson et al. [ 1] from the Multiethnic Cohort Study, the authors reported significant race/ethnicity-specific hazard ratios for the timing of menopause.

Natural menopause occurred earlier among Latinas and later among Japanese-American women relative to non-Latina whites.

The authors further emphasized that these relations are suggestive of a heritable component in the timing of natural menopause.

They concluded by stating, ‘‘. . .

the timing of natural menopause is driven by a combination of genetic, reproductive, and lifestyle factors’’ [1].


This conclusion suggests that the analysis of these data provides some evidence to support the assertion that group difference in the timing of menopause is at least partially driven by genetic factors.

The authors reached this conclusion without stating how racial categories were assigned [2] and without collecting any genetic information.

Although the authors are diplomatic in the overall interpretation of their results, the reference to genetic factors in the concluding statement seems to stem solely from the fact that racial/ethnic groups are compared.

An assertion that racial/ethnic disparities in an outcome suggest genetic differences ignores the complex social context experienced by different racial/ethnic groups.

This tenuous link among genes, race/ethnicity, and health outcomes is often made in the epidemiologic literature without adequately considering other important social and environmental factors that differ between groups [3, 4].


The authors did describe an ancillary analysis in which educational attainment, as a surrogate for socioeconomic status, was included as a covariate, but this is obviously a very coarse measure of the many facets of social environment that may affect the outcome.

In fact, a prior study of factors influencing the age of menopause identified several additional social variables, such as marital status and employment, which played an important role in predicting menopause onset [5].

This previous study also reported associations between race/ethnicity and onset of menopause, but it did not suggest a genetic basis for those differences [5].

In short, the use of race/ethnicity as a proxy for genetic differences in large, heterogeneous populations is unwarranted; drawing conclusions about the role of genetics in biologic processes requires the collection of genetic data.


We thank Mumford and Hasan [1] for their interest in our work [2] and agree with them that racial/ethnic variations do not necessarily imply genetic differences.

In reaching the conclusion that our results support the hypothesis that the timing of natural menopause is driven by a combination of genetic, reproductive, and lifestyle factors, we had in mind the fact that our findings are in line with a growing literature supporting the hypothesis that age at natural menopause is a highly heritable trait [3-9].

We also agree with the need to follow up these findings by searching for specific genetic variants that might contribute to the "genetic" component of age at natural menopause.

Indeed, we are currently engaged in developing candidate gene association studies of age at natural menopause and hope to identify new candidate loci through examination of data from genome-wide association studies, which could then be examined within and across racial/ethnic groups.


The claim that a fifth generation of revolutionary theory has not only already arisen, but has already outlived its purpose is a monumentally bold one.

Despite containing many astute observations, Jaime Allinson's (2019) recent argument to this effect does not adequately support such a claim.

Instead, it mostly targets valid criticisms against newer participants in a prior generation of revolutionary theory, whose analyses are not manifestly different from those we have seen in the past.

In the process of making his argument, Allinson fatally conflates these fourth-generation theories with his proposed new generation.

Despite this crucial flaw, Allinson's corollary argument- that revolutionary theory needs to move on from its present theoretical fixations- is still highly compelling and well supported.


Allinson (2019:143) is keen to impress that his proposed new generation is chiefly distinguished by having incorrectly identified the 2011 Arab Revolts as "a new object of study- that of non-violent, political revolutions." I would contend that such an object of study is precisely the domain of revolutionary theory's fourth generation, which cut its teeth on the analysis of the array of post-Soviet cases in which "there was no need for the revolutionary leaders taking power in the capital to spread their revolution by force," (Goldstone, 2001: 143).

The continuity between this perspective and more recent revolutionary theory is striking and explicit.

Only a few years ago, George Lawson (2015: 466) remarked that the Arab Revolts "share a familiar revolutionary heritage… in terms of wider currents of revolutionary theory," noting that they "sit largely within the framework established by the 1989 negotiated revolutions that ousted state socialism in Central and Eastern Europe." A similar continuity is seen in the texts Allinson recruits for his proposed fifth generation.

Indeed, Allinson notes that Bayat's (2017) analysis in Revolutions without Revolutionaries considers the Arab revolutions to be 'refolutions'.

This term is in fact derived from analyses of the post-Soviet revolutionary wave, in which the revolutionary ideal- tarred by the brush of Communist rule- was considered so politically toxic that the very concept of revolution was either side-lined or consciously rejected during the processes of regime-overthrow and reconstruction (Garton Ash, 1989).

If we are to take Ritter (2015), Bayat (2017) and Della Porta's (2016) objects of study to be "non-violent, political revolutions," as Allinson proposes, then they are most certainly engaged in fourth-generation revolutionary analysis.


Nonetheless, Allinson is certainly correct to suspect that our object of study has changed, and he is right to identify the particular importance of the events of 2011 for future revolutionary theory.

The Arab Spring was not only a new 'revolutionary wave', but was also emblematic of a distinctively different generation of revolutions.

The remarkable subsidence of revolutionary movements in the revolts which characterised the 2011 revolutions has shown, in stark terms, the poverty of existing theoretical perspectives.

Who would have thought, following the example set by the 1989 revolutions and the subsequent Colour Revolutions, that the next revolutionary wave would be carried through by a suite of fleeting revolutionaries who neither knew who their 'leaders' were, nor, in fact, whether they had any?


Many of today's revolutions neither resemble the classical revolutions of the past, nor those of the non- violent post-Soviet wave.

They are, as Allinson (2019:148) rightly notes, often "restricted to the momentary," easily crushed, and particularly vulnerable to counter-revolution.

This, in many ways, is their identifying feature: while the past generation of revolutions were characterised by their non- violence, newer revolutions are characterised by their fragility (we could even collectively call them the 'fragile revolutions').

Some theorists have even deemed them so fragile as to reject their revolutionary prospects altogether.

The political theorist John Dunn, for example, contends that since 1989, all instances of so-called 'revolution' have simply been processes of 'regime collapse,' lacking the strong cast-list of professional revolutionaries required to carry out genuinely transformative change (Abrams & Dunn, 2017; Abrams, 2018).


Despite the importance of these observations, I would affirm that the character of revolutionary waves must be distinguished from generations of revolutionary theory.

While I agree with Allinson that our object of study has decidedly changed, I would also stress that our analytical framework is yet to develop in tandem: current analyses still broadly regard the most recent wave of revolutions as if they were simply failing to follow the marche générale of the post-Soviet revolts, rather than as characterised by their own distinctive paths and dynamics.

In this sense, a novel generation of revolutions is being parsed with an established generation of theory.


Indeed, when we examine the intellectual positions which Allinson ascribes to his candidate generation, it becomes quite clear that his proposed 'fifth-generation' analyses are in fact characterised by fourth- generation traits.

For example, Allinson (2019, 143) contends that his candidate generation has shifted its emphasis to consider "the relationship between intentions, behaviour and structure in revolutions." This outlook is strikingly similar to Foran's observation that "social structure itself must be studied….

by reference to intentional actions." ( 1993:10), and Goldstone's (2001:139) argument that, in addition to structure, revolutionary theory should "incorporate leadership, ideology, and processes of identification with revolutionary movements as key elements in the production of revolution." A similar challenge can be made to Allinson's (2019: 143) suggestion that his new generation of theorists are distinguished by no longer considering revolution to be "a discrete event, capable of being situated on a continuum between social and political change and correlated with the presence or absence of other pre-existing factor[s]." Allinson instead claims that they have opted for a relational approach to the phenomenon.

This is quite a peculiar claim, as the relational approach to which Allinson alludes was considered the defining leap made by "a new fourth generation of scholarship on revolutions and collective action," (Emirbayer & Goodwin 1996, 374) and it has proven to be an agenda to which fourth- generation theorists have consistently returned to over the past three decades (Emirbayer & Goodwin 1996; Parsa, 2000; Goodwin, 2001; Goldstone, 2004; Lawson, 2004, 2016, 2019).

Finally, Allinson (2019:143) makes the argument that his proposed new theoretical generation is distinguished from the past generation by its claim that "revolutions should be understood as processes"- a series of unfolding events- rather than "singular units that can be correlated with other phenomena." This is, again, a well-established fourth-generation perspective: emphasised in Goldstone's revolutionary theorising (2001:152, 2009); established as a cornerstone of the relational approach (Emirbayer, 1997: 281, 304, 309); developed considerably across Charles Tilly's (1978, 1995) life's work; and taking centre stage in Foran's (2005) analysis of 'Third World Revolutions'.

It has been most recently returned to by Lawson (2016) and Ritter (2015) as a direct extension of this legacy.


Part of the reason that Allinson may have been tempted to declare more recent work part of a new, fifth generation is the disparity between what fourth-generation theorists have aspired to achieve, and what they have actually accomplished.

While fourth-generation theory has maintained a relatively consistent overall ontological and epistemological aspiration, its analytical contents are much more varied.

In fact, in contrast to prior generations, the fourth generation of revolutionary theory is a decidedly troubled one.

Despite featuring a plethora of insightful and highly interesting studies, it has ultimately failed to deliver on the early overall promises made by its proponents (Foran, 1993; Goldstone, 2001).

More than a quarter of a century since its inception, the desire to move on seems entirely reasonable.

There are, I argue, three principal obstacles to fourth-generation progress: the overambitious attempt to replace theorising with modelling; the related desire to cover too many variables at once; and the field's displacement by overlapping disciplines.


Fourth-generation revolutionary theory has been characterised by a variety of notable issues which present quite regularly in the associated literature.

The most central of these is the aim of fourth- generation theorists to simultaneously reject bold theorising in favour of iterative work, while also aspiring to build overarching models applicable to the total variety of revolutions across time and space.

When John Foran (1993:16) first heralded the prospects of a new, 'fourth' generation of revolutionary theory, he called for the replacement of grand theory with 'conjunctural modelling', through which periodic, careful case studies would gradually refine overall models of revolution, characterised by multiple facets and variables.

Foran's intention was to pioneer a turn away from mono-causal master- theories in favour of "models more complex and multicausal than the often one-sided arguments" seen in prior work.

In his manifesto for revolutionary theory's fourth generation, Jack Goldstone (2001: 144,172) espoused similar ambitions, declaring that "a full understanding of revolutions must take account of the plasticity of elite and popular alignments, of the processes of revolutionary mobilization and leadership, and of the variable goals and outcomes of revolutionary actors and events." He also declared that "it will treat stability as problematic and focus on the conditions that sustain regimes" while also leaving "a prominent role for issues of identity and ideology, gender, networks and leadership."


Foran and Goldstone's early aspirations for the fourth generation were certainly ambitious. They had called for the wholesale rejection of traditional theorising in favour of a new model-centric approach.

This new approach- were it to succeed- should yield nothing short of a predictive model of revolutions, applicable to an ever increasing historical and geographical variety of cases.

To these theorists' credit, both engaged in concerted attempts to build such a model for some time, before moving on to other projects (Foran, 2005; Goldstone, 1991; 1995).

While Foran and Goldstone's aspirations went on to shape the trajectory of the fourth generation, other fourth-generation theorists expressed substantial concern about this theoretical course of action.

For example, Emirbayer and Goodwin (1996: 360) took a particularly scathing line of critique against Goldstone's (1995) own model, which was supposed to "successfully predict, at least in principle, any and all revolutions." Crushingly, they lambasted the model for ignoring agency, psychology, emotional commitments, culture and politics.

They argued that, under Goldstone's model, "an outside observer need know nothing about a society's cultural systems or extant political ideologies in order to predict whether or not a revolution will occur there…[and] merely scour the local landscape for palpable signs of state crisis, elite conflict, and the possibility of popular protest," (Emirbayer & Goodwin, 1996: 361).


The daunting task of fulfilling Foran and Goldstone's aspirations has invited a peculiar tendency towards introspection among subsequent fourth-generation theorists, making it the most self-monitored generation of theory in the academic study of revolution.

1 This is at least in part a consequence of the coincidence of the idea of theoretical generations with the emergence of a self-consciously 'fourth' generation, but also reflective of the recognisable difficulty of achieving the aims set out for it (Lawson, 2016).

Indeed, many of those studying revolution have declined to engage in such a task, and have instead engaged in more atomistic analyses led by a smaller number of empirical cases, often discursively disconnected from one-another, and theoretically fractured (Beck, 2018).

This process has ushered in an era of fragmented analyses which, though highly worthwhile in their own right, have done little to advance the agenda of fourth-generation scholarship as a whole.


Despite its decline, a recent coalition of scholars have made some praiseworthy attempts to provide life- support to the otherwise faltering fourth generation.

Some, such as Colin Beck (2014), have attempted to move away from classical conjunctural modelling in favour of the development of a multi- dimensional meta-framework.

Others, such as Daniel Ritter (2015) have attempted to focus on the processual and international dynamics of fourth-generation theory.

What is common to both Ritter and Beck's approaches is that they refrain from making naturalistic, predictive claims beyond the realms of the cases they examine, in subtle rejection of the conjunctural approach.

Ritter (2015:223) is especially doubtful of the enduring nature of his finding that the success rates of predominantly non-violent and unarmed revolutions have been strengthened by a liberal world order.

He instead anticipates that the international pendulum may "swing back and make violent struggle against authoritarian states once more the revolutionary's strategy of choice." 2 Still others, such as George Lawson (2016) have attempted to usefully redirect early aspirations in an effort to get the fourth generation back on track, all while expressing a degree of scepticism as to the prospects of the overall project.

Nonetheless, amidst their admiration for the landmark theorists of the fourth generation, reading the work of this newer cohort belies a certain sense of discomfort with their predecessors' endeavours, which I suspect will eventually lead to their breaking with the fourth generation project.


Despite the ground-breaking work of its early theorists (Foran, 1993; Goldstone, 2001), there was, in my view, something mistaken in the fourth generation's attempt to reject bold theory.

This move was in part justified by the notion that past bold theoretical endeavours were somehow irreconcilable and exclusionary, each seeking to promote their own idealised universal cause (Foran, 1993: 16-17 Goldstone, 1980, 2001:171-172).

To the contrary, prior to the advent of fourth generation theory, the 'bold theorists' such as Skocpol (1979), Gurr (1970), Tilly (1978) and Trimberger (1978), consistently emphasised the complexity and contingency of the revolutionary phenomena they studied.


These theorists often sought to argue in favour of the primacy of one factor or another, but did so on the basis of an assumption that other variables also possessed substantial casual force.

Their efforts were more often corrective and exploratory than they were imperialistic.

Skocpol sought to re-centre attention on the State, which she felt had been sorely neglected.

Gurr sought to reassert the primacy of psychological factors, which he rightly observed were lacking in the analysis of revolution.

Tilly sought to draw attention to longer-running political processes, and Trimberger sought to illustrate the important roles played by revolutionary elites.


This is to say that these bold theorists engaged in in-depth investigations of a limited number of variables so as to shed light upon the complex relationships between that variable and revolution's other dimensions.

3 This kind of analytical depth has been comparatively neglected in the bulk of fourth generation theory which, in its efforts to account for an exhaustive list of variables, has all too often lost sight of the logic of their operation.


Co-occurring with the rejection of bold theory, was an ongoing shift in the structure of revolutionary inquiry, characterised by an analytical bias towards geographically and temporally homogenous cases (Beck, 2018), and a corresponding rejection of difference-based comparison by revolutionary analysts.

This had a deleterious effect on the advancement of the very agenda to which fourth-generation theorists aspired, producing- as Beck puts it in his (2018) review of the field- "the conditions under which knowledge accumulation slows." This shift has played a serious role in dampening the field's overall theoretical progress.

Because of the sheer variability of revolutionary phenomena, theoretical development must be situated in the analysis of fundamentally different cases, rather than a suite of highly similar ones.

If an idea is borne out across space, culture and time, then it may well be common to a great many revolutions.

The same cannot be said for something identified amongst a narrow set of historically, geographically or culturally delimited cases.

While, in principle, similar cases can yield theoretical benefits where only a very small and strictly controlled set of variables meaningfully differ between them, in practice, this situation essentially never occurs, even between cases which are as tightly geographically and historically delimited as possible.


While internal maladies have played an important role in the disappointing progress of the fourth generation, its lack of clear advancement has also been a consequence of the displacement of revolutionary study by other, much more populous fields, most particularly the fields of Social Movement Studies and Democratisation.

While it is undeniable that both of these fields have produced highly worthwhile insights about certain elements of revolutions, they do not ultimately regard revolution as their object of study, but instead consider it as containing a sub-form of some other category of events.

In such fields, revolutionary processes are instead regarded as an instance of 'contentious politics'; revolutionary movements are considered 'revolutionary social movements', and 'revolutionary outcomes' are reconceived as cases of 'democratic transition'.