Back to Authors

Salloway, Stephen

https://orcid.org/0000-0002-2631-0942

A5002183686 | I27804330

Mayo Clinic

Dementia Fund, EQT Life Sciences Amsterdam the Netherlands

Citations 115

O4–03–03: Disrupted functional connectivity in autosomal dominant Alzheimer's disease demonstrates network specificity and precedes brain volume loss: Findings from the Dominantly Inherited Alzheimer Network

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_17 | Pages: No page available

10.1016/j.jalz.2013.04.348

IC‐P‐082: Disrupted functional connectivity in autosomal dominant Alzheimer's disease demonstrates network specificity and precedes brain volume loss: Findings from DIAN

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_2 | Pages: No page available

10.1016/j.jalz.2013.05.079

P3–134: Dissociating volume and intensity differences in familial Alzheimer's disease

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_15 | Pages: No page available

10.1016/j.jalz.2013.05.1205

IC‐P‐103: Prevalence and growth of cerebral microhemorrhages in autosomal dominant Alzheimer's disease

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_2 | Pages: No page available

10.1016/j.jalz.2013.05.100

P1–269: Are early atrophy patterns in autosomal dominant familial Alzheimer's disease gene‐dependent?

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_6 | Pages: No page available

10.1016/j.jalz.2013.05.494

IC‐P‐078: Dissociating volume and intensity differences in familial Alzheimer's disease

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_1 | Pages: No page available

10.1016/j.jalz.2013.05.075

O1–03–05: Prevalence and growth of cerebral microhemorrhages in autosomal dominant Alzheimer's disease

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_3 | Pages: No page available

10.1016/j.jalz.2013.04.065

IC‐O1–02: Are early atrophy patterns in autosomal dominant familial Alzheimer's disease gene‐dependent?

Alzheimer's & Dementia | October 9, 2013 | Volume: 9 | Issue: 4S_Part_1 | Pages: No page available

10.1016/j.jalz.2013.04.017

The pattern of atrophy in familial Alzheimer disease

Neurology | September 19, 2013 | Volume: 81 | Issue: 16 | Pages: 1425-1433

10.1212/wnl.0b013e3182a841c6 | PMID 24049139

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

Proceedings of the National Academy of Sciences | March 5, 2013 | Volume: 110 | Issue: 12 | Pages: 4768-4773

10.1073/pnas.1216206110 | PMID 23471985

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.