Robert Jeffrey MacInnis

Dr. Robert Jeffrey MacInnis

orcid

Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2016 in The American Journal of Human Genetics
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Journal Article
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NINilah M. Ioannidis
Nilah M. Ioannidis
JRJoseph H. Rothstein
Joseph H. Rothstein
VPVikas Pejaver
Vikas Pejaver
SMSumit Middha
Sumit Middha
SMShannon K. McDonnell
Shannon K. McDonnell
WSWeiva Sieh
Weiva Sieh

2 December 2010 in New England Journal of Medicine
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Journal Article
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AGAmy Berrington de Gonzalez
Amy Berrington de Gonzalez
PHPatricia Hartge
Patricia Hartge
JCJames Cerhan
James Cerhan
AFAlan J. Flint
Alan J. Flint
LHLindsay Hannan
Lindsay Hannan
MTMichael J. Thun
Michael J. Thun
A high body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) is associated with increased mortality from cardiovascular disease and certain cancers, but the precise relationship between BMI and all-cause mortality remains uncertain. We used Cox regression to estimate hazard ratios and 95% confidence intervals for an association between BMI and all-cause mortality, adjusting for age, study, physical activity, alcohol consumption, education, and marital status in pooled data from 19 prospective studies encompassing 1.46 million white adults, 19 to 84 years of age (median, 58). The median baseline BMI was 26.2. During a median follow-up period of 10 years (range, 5 to 28), 160,087 deaths were identified. Among healthy participants who never smoked, there was a J-shaped relationship between BMI and all-cause mortality. With a BMI of 22.5 to 24.9 as the reference category, hazard ratios among women were 1.47 (95 percent confidence interval [CI], 1.33 to 1.62) for a BMI of 15.0 to 18.4; 1.14 (95% CI, 1.07 to 1.22) for a BMI of 18.5 to 19.9; 1.00 (95% CI, 0.96 to 1.04) for a BMI of 20.0 to 22.4; 1.13 (95% CI, 1.09 to 1.17) for a BMI of 25.0 to 29.9; 1.44 (95% CI, 1.38 to 1.50) for a BMI of 30.0 to 34.9; 1.88 (95% CI, 1.77 to 2.00) for a BMI of 35.0 to 39.9; and 2.51 (95% CI, 2.30 to 2.73) for a BMI of 40.0 to 49.9. In general, the hazard ratios for the men were similar. Hazard ratios for a BMI below 20.0 were attenuated with longer-term follow-up. In white adults, overweight and obesity (and possibly underweight) are associated with increased all-cause mortality. All-cause mortality is generally lowest with a BMI of 20.0 to 24.9.

23 October 2017 in Nature
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KMKyriaki Michailidou
Kyriaki Michailidou
SLSara Lindström
Sara Lindström
JDJoe Dennis
Joe Dennis
JBJonathan Beesley
Jonathan Beesley
SHShirley Hui
Shirley Hui
DEDouglas F. Easton
Douglas F. Easton
Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours. Genome-wide association studies for breast cancer have identified common genetic variation that influences susceptibility to this disease, but much of the genetic risk remains unexplained. Doug Easton and colleagues report a genome-wide association study for breast cancer in more than 122,000 cases and 105,000 controls. The authors genotyped a subset of these cases using OncoArray, a new, custom genome-wide single-nucleotide polymorphism (SNP) array for cancer genomics. Overall, they identify 65 loci newly associated with breast cancer susceptibility, and estimate that, together with 107 previously identified breast cancer susceptibility loci, these explain about 18 per cent of the familial relative risk of breast cancer. Polygenic risk scores may be used in risk prediction models and may improve early detection and targeted prevention of the disease. Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10−8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

1 April 2014 in The American Journal of Clinical Nutrition
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Journal Article
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JWJane E Winter
Jane E Winter
RMRobert Jeffrey MacInnis
Robert Jeffrey MacInnis
NWNaiyana Wattanapenpaiboon
Naiyana Wattanapenpaiboon
CNCaryl Nowson
Caryl Nowson
Whether the association between body mass index (BMI) and all-cause mortality for older adults is the same as for younger adults is unclear. The objective was to determine the association between BMI and all-cause mortality risk in adults ≥65 y of age. A 2-stage random-effects meta-analysis was performed of studies published from 1990 to 2013 that reported the RRs of all-cause mortality for community-based adults aged ≥65 y. Thirty-two studies met the inclusion criteria; these studies included 197,940 individuals with an average follow-up of 12 y. With the use of a BMI (in kg/m2) of 23.0-23.9 as the reference, there was a 12% greater risk of mortality for a BMI range of 21.0-21.9 and a 19% greater risk for a range of 20.0-20.9 [BMI of 21.0-21.9; HR (95% CI): 1.12 (1.10, 1.13); BMI of 20.0-20.9; HR (95% CI): 1.19 (1.17, 1.22)]. Mortality risk began to increase for BMI >33.0 [BMI of 33.0-33.9; HR (95% CI): 1.08 (1.00, 1.15)]. Self-reported anthropometric measurements, adjustment for intermediary factors, and exclusion of early deaths or preexisting disease did not markedly alter the associations, although there was a slight attenuation of the association in never-smokers. For older populations, being overweight was not found to be associated with an increased risk of mortality; however, there was an increased risk for those at the lower end of the recommended BMI range for adults. Because the risk of mortality increased in older people with a BMI <23.0, it would seem appropriate to monitor weight status in this group to address any modifiable causes of weight loss promptly with due consideration of individual comorbidities.

1 March 2017 in Cancer Epidemiology, Biomarkers & Prevention
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AWAung Win
Aung Win
MJMark A. Jenkins
Mark A. Jenkins
JDJames G. Dowty
James G. Dowty
AAAntonis C. Antoniou
Antonis C. Antoniou
ALAndrew Lee
Andrew Lee
RMRobert Jeffrey MacInnis
Robert Jeffrey MacInnis
Background: Although high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods: We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the United States, Canada, and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband's age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of HR for unidentified major gene mutations, and the variance of the residual polygenic component. Results: We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1 = 1 in 1,946, MSH2 = 1 in 2,841, MSH6 = 1 in 758, PMS2 = 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30% to 50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively). Conclusions: Unidentified major genes might explain one third to one half of the missing heritability of colorectal cancer. Impact: Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. Cancer Epidemiol Biomarkers Prev; 26(3); 404–12. ©2016 AACR.

23 October 2017 in Nature Genetics
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AIABCTB Investigators
ABCTB Investigators
RMRoger L Milne
Roger L Milne
EMEmbrace
Embrace
GCGEMO Study Collaborators
GEMO Study Collaborators
HEHebon
Hebon
JSJacques Simard
Jacques Simard
Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population. Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.