Immunogenetic Epidemiology of Motor Neuron Diseases in 14 Continental Western European Countries

Lisa M. James1,2,3, Apostolos P. Georgopoulos1,2,3,4*

1The HLA Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, MN, 55417, USA

2Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN 55455, USA

3Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN 55455, USA

4Department of Neurology, University of Minnesota Medical School, Minneapolis, MN 55455, USA


Very few studies have evaluated associations of human leukocyte antigen (HLA) with motor neuron diseases (MND). Using an immunogenetic epidemiological approach, we identified a population-level HLA profile for MND by evaluating the correlations between the population frequencies of 127 HLA Class I and II alleles and the population prevalence of MND in 14 Continental Western European countries. The results demonstrated that significantly more HLA alleles, particularly for Class I, were negatively associated with the population prevalence of MND, suggesting a preponderance of protective vs susceptibility effects. The findings add to the limited literature implicating HLA in MND and considering the role of HLA in immune system responses to pathogens, suggest a potential influence of pathogens in MND.


Introduction

Motor neuron diseases (MND) are a highly disabling group of neurodegenerative diseases characterized by upper and/or lower motor neuron degeneration. Amyotrophic lateral sclerosis (ALS), which is the most common MND and the most extensively studied, initially involves muscle weakness or stiffness that progresses to gradual loss of voluntary movement with fatality typically occurring within a few years of onset1. Neuropathological features include loss of motor neurons as well as cytoplasmic inclusions that mirror those seen in frontotemporal dementia2. Indeed, as ALS progresses, cognitive symptoms often emerge with varying degrees of impairment up to and including dementia, commonly of the frontotemporal type3,4. Notably, the course, phenotype, and survival time of ALS have been shown to vary geographically in relation to population ancestral origin, pointing towards a modulatory influence of genetic and environmental factors that vary by population5. A number of genes have been implicated in ALS, many of which overlap with frontotemporal dementia6-8. Still, a significant percent of genetic influence of ALS remains unknown, especially in the case of sporadic ALS6. Environmental contributors to ALS are similarly uncertain. Several risk factors including smoking, physical activity, environmental and occupational exposures, head injuries, and diet have been investigated with varying degrees of support9,10. There is increasing evidence implicating microorganisms (e.g., viruses, bacteria) in ALS pathogenesis11. With regard to other MND, all of which are relatively rare, there is considerable heterogeneity in terms of signs, symptoms, and prognosis12. Furthermore, with the exception of spinal muscular atrophy and hereditary spastic paraplegia which are known to have a genetic basis, the cause of other motor neuron diseases is largely unknown12,13

In light of the largely undetermined genetic influence on ALS and other motor neuron diseases and the potential etiological involvement of microorganisms, we focused here on the immunogenetic influence of human leukocyte antigen (HLA), a region of genes on chromosome 6 that are involved in immune response to foreign antigens. The two main classes of HLA – Class I (HLA-A, B, -C) and Class II (HLA-DR, -DQ, DP) - play a critical role in elimination of foreign antigens. Class I presents intracellular antigen peptides to CD8+ cytotoxic T cells which signals destruction of infected cells. Class II presents endocytosed extracellular antigen peptides to CD4+ T cells to promote B-cell mediated antibody production and adaptive immunity. A limited number of studies, largely using low-resolution HLA typing, have evaluated the influence of HLA on ALS with inconsistent findings14. A recent review of the literature indicated primarily Class I associations with ALS14; specifically, HLA-A*03, A*02, A*28; B*40, B*35, and C*04 have been found to promote susceptibility whereas A*09 is protective. A recent study in a Chinese population reported risk associated with a single nucleotide polymorphism in the DR gene, suggesting a role for HLA Class II in ALS15. These findings suggest an immunogenetic component to ALS; however, further study of HLA associations with ALS and other MND is warranted. The highly polymorphic nature of HLA presents a challenge in terms of identifying specific alleles that may be associated with rare diseases such as MNDs at the individual level. Therefore, we are utilizing a population immunogenetic approach to identify an HLA profile with regard to MND prevalence to better understand risk and protection associated with a wide range of HLA alleles. We have used a similar approach to identify HLA profiles for dementia, Parkinson’s disease, multiple sclerosis, and Type 1 diabetes16-20. This approach takes advantage of the population heterogeneity of HLA and utilizes high-resolution HLA genotyping to determine HLA alleles that are presumed to be protective (i.e., negatively associated) or susceptible (i.e., positively correlated) with regard to the population prevalence of a disease. 

Materials and Methods

Prevalence of MND

The population prevalence of MND was computed for each of the following 14 countries in Continental Western Europe: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Italy, Netherlands, Portugal, Norway, Spain, Sweden, and Switzerland. Specifically, the total number of people with MND in each of the 14 Continental Western European countries as determined by the Global Burden of Disease study21 was divided by the total population of each country in 2016 (Population Reference Bureau)22 and expressed as a percentage. The Global Burden of Disease study included ALS, spinal muscular atrophy, hereditary spastic paraplegia, primary lateral sclerosis, progressive muscular atrophy, and pseudobulbar palsy in its evaluation of the population characteristics of MND. We have previously shown that life expectancy for these countries is virtually identical17; therefore, life expectancy was not included in the current analyses. 

HLA

The frequencies of all reported HLA alleles of classical genes of Class I (A, B, C) and Class II (DPB1, DQB1, DRB1) for each of the 14 Continental Western European countries were retrieved from the website allelefrequencies.net (Estimation of Global Allele Frequencies23,24) on October 20, 2020. There was a total of 2746 entries of alleles from the 14 Continental Western European countries, comprising 844 distinct alleles. Of those, 127 alleles occurred in 9 or more countries and were used in further analyses. This criterion is somewhat arbitrary but reasonable, since it encompasses ≥ 64.3% (≥ 9/14) of the whole sample of 14 countries. In addition, it was partially validated in a previous study16, where HLA-disease associations for dementia and Parkinson’s disease were congruent across a range of sample sizes.

The distribution of those alleles to the HLA classes and their genes is given in Table 1. 

Table 1: Distribution of 127 HLA alleles analyzed to Class and Genes.

 

Class I (N = 69)

Class II (N = 58)

Gene

A

B

C

DPB1

DQB1

DRB1

Count

20

36

13

15

14

29

Data analysis

HLA profiles for MND were derived as described previously for other diseases16-20. Briefly, the prevalence of MND in a country was computed as the fraction of total country population and was expressed as a percentage. MND prevalences were natural-log transformed and the Pearson correlation coefficient, r, between MND prevalence and the population frequency of each one of the 127 HLA alleles above calculated and Fisher z−transformed25 to normalize its distribution:

                                                r´ = atanh(r)                        (1)

The MND HLA profile consisted of 127 values of r´. The effects of HLA Class and gene (within a class) on r´ were evaluated using a univariate analysis of variance (ANOVA). Finally, differences in the proportions of the counts of negative and positive r´ were evaluated using the Wald H0 statistic for comparing proportions of independent samples. Statistical analyses were performed using the IBM−SPSS package (IBM SPSS Statistics for Windows, Version 26.0, 64−bit edition. Armonk, NY: IBM Corp; 2019) and Intel FORTRAN (Microsoft Visual Studio Community Version 16.8.3; Intel FORTRAN Compiler 2021).

Results

As mentioned above, the MND HLA profile consists of correlations between allele frequency and disease prevalence, suitably Fisher z-transformed (Equation 1) to normalize their distribution for further analyses. We showed previously17 that dementia prevalence varies in an exponential fashion with allele frequency, such that the logarithm of disease prevalence is a linear function of allele frequency. We found the same relation here between MND prevalence and HLA allele frequency. Two examples are illustrated in Figs. 1 and 2, namely for a presumed MND protective allele (A&26:01) and a susceptibility allele (B*40:01) (Fig. 1A and B, respectively).

JISS-21-1221-fig1

Figure 1: Example from a presumed protective HLA allele (A*26:01) and a presumed susceptibility allele (B*40:01) for MND. A, log-transformed MND prevalence (%) for 11 CWE countries is plotted against the corresponding frequency of the A*26:01 (P =0.0005). B, log-transformed MND prevalence (%) for 12 CWE countries is plotted against the corresponding frequency of the B*40:01 (P =0.0005).

HLA-MND profile

The frequency distribution of alleles in the HLA MND profile (Table 2) is shown in Fig. 2. There were 76/127 (59.8%) negative (protective) alleles and 51/127 (40.2%) positive (susceptibility) alleles. These percentages differed significantly from the null hypothesis of 50% (P = 0.027, two-sided one-sample binomial test; z = 2.218).

JISS-21-1221-fig2

Figure 2. Frequency distribution of MND HLA profile (N = 127).

The distributions of r´ for Class I and II are shown in Fig. 3. There were 69/127 (54.3%) r´ in Class I and 58/127 (46.7%) in Class II; these percentages did not differ significantly from the 50-50% null hypothesis (P = 0.329, two-sided one-sample binomial test; z = 0.976). For Class I, there were 45/69 (65.2%) negative (protective) and 24/69 (34.8%) positive (susceptibility) values, respectively; these percentages differed significantly from the 50-50% null hypothesis (P = 0.011, two-sided one-sample binomial test; z = 2.528). For Class II, there were 31/58 (53.4%) negative and 27/58 (46.6%) positive values, respectively; these percentages did not differ significantly from the 50-50% null hypothesis (P = 0.599, two-sided one-sample binomial test; z = 0.535).

JISS-21-1221-fig3

Figure 3. HLA Class distributions of MND HLA profile. N = 69 alleles for Class I and 58 alleles for Class II.

Table 2. HLA profile of MND. The signed z-transformed correlation coefficient (r´) between 127 HLA alleles and ln (MND) prevalence. N denotes the number of CWE countries from which r´ was calculated.

 

Allele

Class

N

r´(MND)

1

A*01:01

I

11

−.360

2

A*02:01

I

11

0.402

3

A*02:05

I

9

−0.193

4

A*03:01

I

11

1.080

5

A*11:01

I

11

−0.682

6

A*23:01

I

11

−0.636

7

A*24:02

I

11

0.158

8

A*25:01

I

12

0.083

9

A*26:01

I

11

−1.322

10

A*29:01

I

11

−0.016

11

A*29:02

I

11

0.003

12

A*30:01

I

11

−0.426

13

A*30:02

I

12

−0.180

14

A*31:01

I

9

0.929

15

A*32:01

I

12

−1.282

16

A*33:01

I

10

−0.116

17

A*33:03

I

9

−0.957

18

A*36:01

I

10

−0.354

19

A*68:01

I

11

−0.094

20

A*68:02

I

10

−0.132

21

B*07:02

I

10

1.118

22

B*08:01

I

12

0.407

23

B*13:02

I

11

−0.269

24

B*14:01

I

11

−0.040

25

B*14:02

I

10

−0.104

26

B*15:01

I

10

1.187

27

B*15:17

I

9

−0.159

28

B*15:18

I

9

−0.272

29

B*18:01

I

12

−0.870

30

B*27:02

I

10

0.182

31

B*27:05

I

12

0.672

32

B*35:01

I

11

0.025

33

B*35:02

I

9

−0.577

34

B*35:03

I

9

−1.046

35

B*35:08

I

9

−0.830

36

B*37:01

I

10

1.180

37

B*38:01

I

9

−0.937

38

B*39:01

I

11

−0.356

39

B*39:06

I

9

−0.147

40

B*40:01

I

12

1.247

41

B*40:02

I

12

0.294

42

B*41:01

I

11

−0.321

43

B*41:02

I

10

−0.585

44

B*44:02

I

12

0.064

45

B*44:03

I

12

−0.154

46

B*44:05

I

9

−0.843

47

B*45:01

I

10

0.219

48

B*47:01

I

11

−0.193

49

B*49:01

I

11

−0.726

50

B*50:01

I

10

−0.331

51

B*51:01

I

10

−0.860

52

B*52:01

I

10

−0.871

53

B*55:01

I

11

0.324

54

B*56:01

I

9

0.660

55

B*57:01

I

12

−0.594

56

B*58:01

I

9

−0.652

57

C*01:02

I

9

0.510

58

C*03:03

I

9

1.123

59

C*04:01

I

9

−0.762

60

C*05:01

I

9

0.509

61

C*06:02

I

9

−0.542

62

C*07:01

I

9

0.027

63

C*07:02

I

9

1.098

64

C*07:04

I

9

−0.589

65

C*12:02

I

9

−0.897

66

C*12:03

I

9

−1.158

67

C*14:02

I

9

−0.943

68

C*15:02

I

9

−0.909

69

C*16:01

I

9

−0.0005

70

DPB1*01:01

II

11

0.946

71

DPB1*02:01

II

11

−0.934

72

DPB1*02:02

II

10

−0.148

73

DPB1*03:01

II

11

0.165

74

DPB1*04:01

II

11

0.545

75

DPB1*04:02

II

11

−0.190

76

DPB1*05:01

II

11

0.747

77

DPB1*06:01

II

10

0.289

78

DPB1*09:01

II

9

−0.183

79

DPB1*10:01

II

10

−0.567

80

DPB1*11:01

II

9

0.133

81

DPB1*13:01

II

10

−0.825

82

 DPB1*14:01 

II

11

−0.918

83

 DPB1*17:01 

II

9

−0.315

84

 DPB1*19:01 

II

11

0.415

85

 DQB1*02:01 

II

12

0.533

86

 DQB1*02:02 

II

11

−0.278

87

 DQB1*03:01 

II

13

−1.059

88

 DQB1*03:02 

II

13

0.981

89

 DQB1*03:03 

II

13

0.722

90

 DQB1*04:02 

II

13

0.800

91

 DQB1*05:01 

II

13

0.154

92

 DQB1*05:02 

II

10

−1.206

93

 DQB1*05:03 

II

12

−0.612

94

 DQB1*06:01 

II

11

−0.371

95

 DQB1*06:02 

II

14

0.733

96

 DQB1*06:03 

II

13

0.310

97

 DQB1*06:04 

II

12

0.048

98

 DQB1*06:09 

II

9

−0.022

99

 DRB1*01:01 

II

14

0.538

100

 DRB1*01:02 

II

11

−0.477

101

 DRB1*01:03 

II

11

−0.389

102

 DRB1*03:01 

II

13

−0.004

103

 DRB1*04:01 

II

13

0.666

104

 DRB1*04:02 

II

11

−0.732

105

 DRB1*04:03 

II

12

−0.952

106

 DRB1*04:04 

II

13

0.833

107

 DRB1*04:05 

II

9

−0.189

108

 DRB1*04:07 

II

12

−0.145

109

 DRB1*04:08 

II

9

0.798

110

 DRB1*07:01 

II

12

−0.396

111

 DRB1*08:01 

II

13

0.779

112

 DRB1*08:03 

II

11

0.107

113

 DRB1*09:01 

II

12

0.566

114

 DRB1*10:01 

II

14

0.004

115

 DRB1*11:01 

II

14

−0.354

116

 DRB1*11:02 

II

12

−0.252

117

 DRB1*11:03 

II

12

−1.002

118

 DRB1*11:04 

II

12

−0.781

119

 DRB1*12:01 

II

13

0.614

120

 DRB1*13:01 

II

14

0.694

121

 DRB1*13:02 

II

14

0.160

122

 DRB1*13:03 

II

10

−0.862

123

 DRB1*13:05 

II

10

−0.214

124

 DRB1*14:01 

II

14

−0.471

125

 DRB1*15:01 

II

13

0.689

126

 DRB1*15:02 

II

10

−1.206

127

 DRB1*16:01 

II

10

−0.899

Note. Strongest associations are denoted in bold.

Analysis of strength of r´

There were no statistically significant differences in the strength of r´ (|r´|) between the protective and susceptibility groups for either HLA class or gene (within a class) (P>0.05 for all comparisons, independent samples t-test).

Discussion

In the present study we used an immunogenetic epidemiological approach across 14 countries in Continental Western Europe to identify a population−level HLA profile consisting of protective and susceptibility alleles for MND. Few prior studies have evaluated HLA associations with ALS or other MND and most of those have focused on Class I alleles. Here we identified robust HLA-MND associations particularly involving Class I alleles but also several strong associations with Class II alleles. These findings, which suggest a broader influence of HLA on MND beyond the small number of Class I alleles that have been previously documented to be associated with MND, are discussed below.

Nearly 60% of the HLA alleles investigated here were negatively associated with the population prevalence of MND and presumed to be protective. Moreover, for Class I alleles in particular there were significantly more protective alleles than susceptibility alleles; Class II alleles did not significantly differ in terms of protection vs susceptibility. The relative rarity of MNDs26 may be partially related to the preponderance of protective (i.e., negatively correlated) alleles observed in the present study. These findings notably stand in contrast to prior research using the same approach that demonstrated a preponderance of susceptibility alleles in both dementia and Parkinson’s disease, two conditions that are much more frequent than MND16. Previous research has documented protective effects for A*0927. The current analyses included only those alleles that were present in at least 9 of the 14 countries; thus, A*09 was not included in the present analyses. Here, the strongest protective effects (i.e., negative correlations with the population prevalence of MND) were found for three Class I alleles (A*26:01, A*32:01, C*13:02) and for two Class II alleles (DRB1*15:02 and DQB1*05:02). In light of the evolutionary role of HLA in host protection from foreign antigens such as viruses and bacteria via T- cell and B-cell mediated immune mechanisms, we presume that the protective effects of Class I and Class II HLA alleles observed here are related to elimination of pathogens that have been implicated in MND11

We have previously proposed that pathogen exposure in the absence of protective HLA results in persistent antigens that may promote disease through direct damage to cells and/or, in the presence of HLA susceptibility alleles, autoimmunity due to chronic inflammation16. With regard to ALS, accumulating evidence indicates autoimmune mechanisms against motor nerve terminals and voltage-dependent calcium channels result in apoptosis and neuronal death28. In addition, increased Class II HLA-DR expression in peripheral nerves of ALS patients has been suggested to reflect an autoimmune mechanism targeting Schwann cells29. Furthermore, evidence of inflammation in ALS as indicated by an increase in the number of microglial cells and reactive microglia displaying high levels of Class I and Class II HLA30,31. In the present study, both Class I and Class II HLA were associated with increased population prevalence of MND. The strongest positive associations were found for Class I alleles including B*07:02, B*15:01, B*37:01, B*40:01, C*03:03. Previous research has identified increased risk associated with B*40 as well as A*02, A*03, A*28, B*35, and C*0412, most of which were also associated with population susceptibility in the current study. 

ALS, the most common MND, is considered to be part of a continuum with other neurodegenerative diseases including frontotemporal dementia and Parkinson’s disease10. The current findings suggest that immunogenetic mechanisms are part of that continuum. Indeed, similar to the present findings, HLA has been implicated in the population prevalence of several other neurodegenerative conditions including dementia, Parkinson’s disease, and multiple sclerosis16-20. Considering the evolutionary role of HLA in immune response to foreign antigens, these studies suggest a common role of foreign antigens (e.g., viruses, bacteria) in these neurodegenerative conditions. Work is ongoing in our lab to evaluate in silico the binding affinity of candidate antigens with specific HLA alleles32,33

Identification of HLA-MND associations at the individual level is hampered by the infrequency of MND and the extreme polymorphism of HLA; prohibitively large samples of MND patients would be required to evaluate MND associations with the wide range of HLA alleles investigated here. In addition, the few prior studies evaluating HLA in relation to MND have often been limited by reliance on low-resolution HLA typing which masks important protein-level differences in disease associations. For instance, in the present analyses, DRB1*15:01 was positively associated with MND whereas DRB1*15:02 was negatively associated with MND. Protein level differences have been shown to alter the binding groove, shaping the repertoire of antigens that can bind and stimulate an immune response34. The current population level approach permits evaluation of numerous high−resolution Class I and Class II HLA alleles with MND prevalence. In addition, inclusion of data from several countries increases allele diversity and regional generalizability of the findings. That being said, the HLA-MND associations observed in these 14 Continental Western European countries may not extend to other regions given population variability in HLA35,36. In addition, our analyses are based on the Global Burden of Disease Study population counts of several conditions classified together as MND; however, HLA associations with each specific MND may vary and disease-specific HLA associations are not evaluated here. Finally, the analyses are based on correlations between the population frequency of HLA alleles and the population prevalence of MND; while the results provide compelling evidence of robust HLA-MND associations at the population level, additional studies are warranted to determine causal associations. We assume that HLA-MND associations implicate pathogens as a contributor to MND given the evolutionary role of HLA in pathogen elimination; however, the influence of specific pathogens on HLA-MND associations remains to be determined. 

Conclusion

Compared to other neurodegenerative conditions research evaluating HLA associations with MND is limited. Here we evaluated immunogenetic influences on MND at the population level. The findings support a role of Class I and Class II HLA in the population prevalence of MND and extend the existing literature to identify a number of susceptibility and protective alleles. Considering the role of HLA in immune system responses to foreign antigens, these findings point to a potential contributory role of pathogens in MND. 

Acknowledgments

Partial funding for this study was provided by the University of Minnesota (the Anita Kunin Chair in Women's Healthy Brain Aging, the Brain and Genomics Fund, the McKnight Presidential Chair of Cognitive Neuroscience, and the American Legion Brain Sciences Chair) and the U.S. Department of Veterans Affairs. The sponsors had no role in the current study design, analysis or interpretation, or in the writing of this paper. The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. 

Conflicts of Interest

None. 

Author Contributions

APG analyzed the data. LMJ and APG wrote the paper. 

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Article Info

Article Notes

  • Published on: August 19, 2021

Keywords

  • Motor neuron diseases

  • Human leukocyte antigen
  • Epidemiology
  • Immunity
  • Genetics

*Correspondence:

Dr. Apostolos P. Georgopoulos,
Brain Sciences Center (11B), Minneapolis VAHCS, One Veterans Drive, Minneapolis, MN 55417, USA;
Email: omega@umn.edu

©2021 Georgopoulos AP. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.