Autoimmune Disease Clusters in Families
A study on familial pairs with autoimmune disease, polyautoimmunity and Multiple autoimmune syndrome.
I missed posting on Friday because my whole family came down with a GI illness and reminded me how true my post last week was—humans are fundamentally food tubes, and sometimes the externality of that system intrudes in unpleasant ways. Thank you so much for subscribing—I truly appreciate your readership.
Today’s study is from the polyautoimmunity/Multiple autoimmune syndrome researcher Anaya—and co-authors. Anaya, along with a varied collection of co-authors, has, by far, the most publications on Multiple autoimmune syndrome of any author in the past 15 years. His research provides a template for the path forward for autoimmune disease research, including an emphasis on molecular genetic analysis. This study of clusters of autoimmune diseases within families points to new avenues for genetic studies that could identify contributing or causative genes within families. The study reviewed today was published the same year as his study on Whole Exome Sequencing of participants with Multiple autoimmune syndrome. That study found 9 completely-new-to-science variants, some of which were shared among study participants, and recommended further genetic study within families. This study on familial clustering of autoimmune diseases suggests that the most fruitful avenue for further study is in genetic testing of sister/sister pairs in families with a clustering of autoimmune diseases.
Area of Investigation
Multiple Autoimmune Syndrome: when one person meets the study classification criteria for three or more autoimmune diseases.
Study Title
Familial Aggregation and Segregation Analysis in Families Presenting Autoimmunity, Polyautoimmunity, and Multiple Autoimmune Syndrome
Results
127 late-onset families and 83 early-onset families were studied for family clustering of autoimmune disease, polyautoimmunity and multiple autoimmune syndrome. Early onset is defined as any family in which the presenting disease was Type 1 diabetes. Late onset is defined as any family in which the presenting disease was an autoimmune disease other than Type 1 diabetes. I’m skeptical about how useful this distinction is, and whether the comparison between the two advances applicable knowledge of varied autoimmune disease.
443 individuals from early onset families were included. 716 individuals from late onset families were included. Analysis was restricted to first-degree relatives: parent/children and sibling/sibling pairs.
Familial Pair Results
When considering autoimmune disease within the late-onset families, clustering of autoimmune disease among first degree relatives—both parent/offspring and sibling/sibling—was significant.
Of 876 parent/offspring pairs: 55 pairs had autoimmune disease; 190 pairs did not have autoimmune disease; and 208 pairs were “discordant” (one family member with autoimmune disease, and one family member without autoimmune disease).
Of 706 sibling/sibling pairs, 86 pairs had autoimmune disease, 267 pairs did not have autoimmune disease, and 353 pairs were discordant.
Of 336 sister/sister pairs: 67 pairs had autoimmune disease; 92 pairs did not have autoimmune disease; and 177 pairs were discordant.
Of 306 brother/sister pairs: 19 pairs had autoimmune disease; 131 pairs did not have autoimmune disease; and 156 pairs were discordant.
Of 64 brother/brother pairs: 0 pairs had autoimmune disease; 44 pairs did not have autoimmune disease; and 20 pairs were discordant.
As is evident from the data, “aggregation of autoimmune disease in late-onset families had the highest aggregation within sister pairs.” I’m also struck by the disparity between the number of sister/sister pairs (336) and brother/brother (64) pairs in the late-onset families included in this study. The female predominance of late-onset families affected by autoimmune disease, polyautoimmunity and multiple autoimmune syndrome (MAS) compared to early-onset families is noted by the study authors:
Late-onset families included 37% males and 63% females while early-onset presented 51% males and 49% females. Moreover, females represented the most affected ones in late-onset families while in early-onset the ratio of the affected was close to 1 : 1 (male : female). In early-onset families, there was only one individual presenting with MAS among the 102 affected individuals.
When considering polyautoimmunity within late-onset families, significant clustering was not observed in parent/offspring pairs, but was observed in sister/sister pairs:
of 876 parent/offspring pairs: 8 pairs had polyautoimmunity; 333 pairs did not have polyautoimmunity; and 112 pairs were discordant.
of 706 sibling/sibling pairs, 23 pairs had polyautoimmunity, 450 pairs did not have polyautoimmunity, and 233 pairs were discordant.
of 336 sister/sister pairs: 20 pairs had polyautoimmunity; 181 pairs did not have polyautoimmunity; and 135 pairs were discordant.
of 306 brother/sister pairs: 1 pair had polyautoimmunity; 261 pairs did not have polyautoimmunity; and 44 pairs were discordant.
of 64 brother/brother pairs: 0 pairs had polyautoimmunity; 59 pairs did not have polyautoimmunity; and 5 pairs were discordant.
When considering Multiple autoimmune syndrome within late-onset families, no significant clustering among any pairs of family members was observed:
of 876 parent/offspring pairs, 1 pair had Multiple autoimmune syndrome, 403 pairs did not have Multiple autoimmune syndrome, and 49 pairs were discordant.
of 706 sibling/sibling pairs, 4 pairs had Multiple autoimmune syndrome, 581 pairs did not have Multiple autoimmune syndrome, and 121 pairs were discordant.
of 336 sister/sister pairs, 3 pairs had Multiple autoimmune syndrome, 260 pairs did not have Multiple autoimmune syndrome, and 73 pairs were discordant.
of 306 brother/sister pairs, 1 pair had Multiple autoimmune syndrome, 261 pairs did not have Multiple autoimmune syndrome, and 44 pairs were discordant.
of 64 brother/brother pairs, 0 pairs had Multiple autoimmune syndrome, 60 pairs did not have Multiple autoimmune syndrome, and 4 pairs were discordant.
When considering autoimmune disease within early-onset families, the clustering of autoimmune disease was less significant than in late-onset families, but still present.
Of 498 parent/offspring pairs: 9 pairs had autoimmune disease; 199 pairs had no autoimmune disease; 155 pairs were discordant.
Of 245 sibling/sibling pairs: 9 pairs had autoimmune disease; 130 pairs had no autoimmune disease; 106 pairs were discordant.
61 sister/sister pairs: 3 pairs had autoimmune disease; 30 pairs had no autoimmune disease; 28 pairs were discordant.
120 brother/sister pairs: 4 pairs had autoimmune disease; 67 pairs had no autoimmune disease; 53 pairs were discordant.
60 brother/brother pairs: 2 pairs had autoimmune disease; 33 pairs had no autoimmune disease; 25 pairs were discordant.
There was no clustering of polyautoimmunity or Multiple autoimmune syndrome found within early-onset families in this study.
Theoretical Mathematical Genetic Modeling
The authors used genetic modeling to assess the data on clusters of autoimmune disease, polyautoimmunity and Multiple autoimmune syndrome within families. Anyone with any education on genetic modeling is more qualified than I am to assess the veracity of the various models that the authors used—I have zero background in statistics or genetic modeling. I am sure that there is ample room for error in this type of theoretical modeling, but I think the attempt at understanding genetic inheritance of autoimmunity is incredibly interesting.
Most interesting to me is that, based on their modeling, random genetic transmission of autoimmune disease, polyautoimmunity and Multiple autoimmune syndrome was able to be ruled out in late-onset families. When they used additional modeling techniques to further test theoretical genetic transmission in late-onset families, their results pointed to a “major gene” as a causative factor in polyautoimmunity and Multiple autoimmune syndrome in genetic transmission among late-onset families. The “major gene hypothesis” was rejected by their modeling for singular autoimmune disease. I take this rejection to mean that there may be many minor genes contributing to genetic transmission, or that environmental factors may play a bigger role in autoimmune disease development according to this modeling.
In contrast, genetic modeling in early-onset families did not rule out random genetic transmission of autoimmune disease among family members, but the modeling also supported that a “major gene” could be responsible for genetic transmission of autoimmune disease among family members. Polyautoimmunity and Multiple autoimmune syndrome as main traits were not modeled due to low frequency.
Why it Matters
There are a number of reasons why proving, and characterizing, genetic transmission of autoimmune disease, polyautoimmunity and Multiple autoimmune syndrome is important. It strengthens the suspicion for autoimmune disease in patients with a family member with autoimmune disease. The history of autoimmune disease diagnosis shows that identification of contributing, or causative genes, can be the definitive factor in the diagnosis of autoimmune disease. Identifying contributing, or causative genes, has the potential to define the root cause of autoimmune disease, and shape therapy that targets the malfunctioning process, instead of the resultant signs and symptoms.
Study Type
For reference, I have ranked medical study types in order of least likely to be affected by hidden bias to most likely to be affected. Those studies that are most likely to be affected by hidden bias should be taken seriously, but not given the same weight as studies that are less likely to be affected by hidden bias. This study’s type appears in bold below.
Clinical Trial
Observational Study
Prospective
Retrospective
Cross-sectional
References
Castiblanco J, Sarmiento-Monroy JC, Mantilla RD, Rojas-Villarraga A, Anaya JM. Familial Aggregation and Segregation Analysis in Families Presenting Autoimmunity, Polyautoimmunity, and Multiple Autoimmune Syndrome. J Immunol Res. 2015;2015:572353. doi: 10.1155/2015/572353. Epub 2015 Nov 30. PMID: 26697508; PMCID: PMC4677210.