Clustering of non-major histocompatibility complex susceptibility candidate loci in human autoimmune diseases

K Becker

R Simon

J Bailey-Wilson

B Freidlin

W Biddison

H McFarland

J Trent

^{Cancer Genetics Branch, National Human Genome Research Institute,}^{Biometric Research Branch, National Cancer Institute, and}^{Neuroimmunology Branch, National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda, MD 20892;}^{Section of Statistical Genetics, Center for Inherited Disease Research, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224; and}^{The Emmes Corp., Potomac, MD 20854}

^{To whom reprint requests should be addressed at: Cancer Genetics Branch, National Human Genome Research Institute, 49 Convent Drive, Room 4B11, Bethesda, MD 20892-4470. e-mail:}vog.hin.irghn@rekcebk.

Communicated by Francis S. Collins, National Institutes of Health, Bethesda, MD

Received 1998 Apr 30; Accepted 1998 Jun 17.

Abstract

Human autoimmune diseases are thought to develop through a complex combination of genetic and environmental factors. Genome-wide linkage searches of autoimmune and inflammatory/immune disorders have identified a large number of non-major histocompatibility complex loci that collectively contribute to disease susceptibility. A comparison was made of the linkage results from 23 published autoimmune or immune-mediated disease genome-wide scans. Human diseases included multiple sclerosis, Crohn’s disease, familial psoriasis, asthma, and type-I diabetes (IDDM). Experimental animal disease studies included murine experimental autoimmune encephalomyelitis, rat inflammatory arthritis, rat and murine IDDM, histamine sensitization, immunity to exogenous antigens, and murine lupus (systemic lupus erythematosus; SLE). A majority (≈65%) of the human positive linkages map nonrandomly into 18 distinct clusters. Overlapping of susceptibility loci occurs between different human immune diseases and by comparing conserved regions with experimental autoimmune/immune disease models. This nonrandom clustering supports a hypothesis that, in some cases, clinically distinct autoimmune diseases may be controlled by a common set of susceptibility genes.

Abstract

Autoimmune diseases are common chronic conditions that involve immune attack of one or more organ systems and affect approximately 5% of the population. The specific etiologies of virtually all human autoimmune diseases are unknown, although they are thought to arise through a complex combination of genetic and environmental factors. Several reviews of autoimmunity and autoimmune diseases have recently been published (1–3).

One of the central genetic factors recognized in autoimmune diseases is the major histocompatibility complex (MHC). Recently, MHC and non-MHC genetic loci have been identified through genome scanning methods in autoimmune or inflammatory animal models and in human diseases. These include multiple sclerosis (MS) (4–7), IDDM (8–10), Crohn’s disease (CD) (11, 12), familial psoriasis (PS) (13, 14), asthma (AS) (15), rat inflammatory arthritis (16), murine lupus (SLE) (17, 18), and experimental autoimmune encephalomyelitis (EAE) (19, 20). Linkage results from genome scans for autoimmune/immune disorders tend to have complex patterns as compared with traditional linkage studies of monogenic traits (21). Autoimmune genome-wide scans report a greater number of linked loci (≈5–20) of lower significance levels, suggesting a complex genetic etiology.

Guidelines for interpretation of genome scan results have been described to provide standard criteria for reporting linkage data (22). By these criteria, for monogenic Mendelian traits, P values of less than 0.05 in a complete genome scan are recognized as potentially significant with logarithm of odds (lod) scores >1.0 and χ^{values >4.0 commonly reported. In contrast, candidate loci from gene scans of complex diseases, including autoimmune disease, are more speculative, with frequent mapping of multiple loci, often covering wide physical distances (10–40 cM).}

Here we have compared the map location of all non-MHC candidate loci from published studies of autoimmune diseases by using suggestive, significant, and highly significant (22) linkage estimations. These loci fall into 18 clusters, suggesting a possible shared genetic basis among different autoimmune diseases.

There are many common elements among clinically distinct autoimmune diseases, including population frequencies (2), geographical distributions (23), clinical features (24), and therapeutic strategies. Most autoimmune diseases are thought to involve altered functions of humoral or cellular immunity. A sex ratio other than 1 in autoimmune disease is common, with women representing ≈75% of autoimmune patients (24). Familial clustering of different autoimmune diseases (2, 25), and coassociation of multiple autoimmune diseases in individuals has been frequently reported. The occurrence of common features of autoimmune diseases and the coassociation of multiple autoimmune diseases in the same individual or family supports the notion that there may be common genetic factors that predispose to autoimmunity. Vyse and Todd (2) have shown significant overlapping of susceptibility loci for autoimmune diseases in mouse.

In this study, a comparison was made between 23 autoimmune or inflammatory genome-wide scans or linkage studies. Human autoimmune diseases included MS (4–7), CD (11, 12), PS (13, 14), AS (15), and human type-I diabetes (IDDM-H) (8, 10, 26, 27). Animal disease studies included EAE (19, 20), rat inflammatory arthritis (16), rat IDDM (IDDM-R) (9), murine IDDM (IDDM-M) (28, 29), Bordetella pertussis-induced histamine sensitization (30), immunity to exogenous antigens (31), and murine SLE (17, 18). As controls, seven nonautoimmune human disease genome scans performed in a similar manner were also included. These included human type II diabetes (NIDDM) (32), schizophrenia (SZ) (33, 34), bipolar (BP) disorder (35, 36), leptin-associated obesity (37), and hypertension (HT) (38).

There were marked differences between most of these studies in experimental design, patient populations, sample size, markers used, and calculations of results. However, despite the use of different analytic approaches, these studies come to similar conclusions; namely, that in almost all common autoimmune/inflammatory diseases there may be no single genes exerting a predominate effect. Nonetheless, there do appear to be multiple loci of less significance that are candidates in the complex genetic etiology of these diseases.

Cl, Cluster; Chrom/Marker, human chromosome, marker or marker gene. Homologs of mouse or rat marker genes were used for cross-species comparisons. In some cases, the centiMorgan distance from the rodent centromere was used for homology comparisons to human gene maps. Rodent markers (in parentheses). Markers in bold are identical markers used in separate studies; Sp, Species; C, used for statistical significance; Ex, Exceptions to contiguous interval and cluster definition Dis, disease; MS, multiple sclerosis; CD, Crohn disease; CD/UC, Crohn disease/ulcerative colitis; EAE, experimental autoimmune encephalomyelitis; IA, inflammatory arthritis; PS, psoriasis; IDDM, insulin-dependent diabetes melitis; AS; asthma; HR, B. pertussis-induced histamine sensitization; HI, humoral immunity; SLE; systemic lupus erythematosus. Ch.reg., cytogenetic band; LDB–gmaps; na, not available; lod or χ^{lod scores or χ}^{; cM-phym, distance from the top of the human chromosome in centimorgans; LDB–gmaps, na, in cross-species comparisons.}

See Table Table11 legend for key to abbreviations.

Acknowledgments

We thank Drs. W. Bias, E. Blankenhorn, P. Meltzer, G. Papanicolaou, N. Rose, C. Teuscher, and J. Todd for reading the manuscript. We thank D. Leja for graphic assistance.

Acknowledgments

ABBREVIATIONS

MHC	major histocompatibility complex
MS	multiple sclerosis
IDDM	type-I diabetes
CD	Crohn’s disease
PS	familial psoriasis
AS	asthma
EAE	experimental autoimmune encephalomyelitis
lod	logarithm of odds
PM	positive marker
cI	contiguous interval
SZ	schizophrenia
BP	bipolar
HT	hypertension
LP	leptin-associated obesity
systemic lupus erythematosus.

ABBREVIATIONS

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