Back

DNA Methylation-Derived Immune Cell Proportions and Cancer Risk, Including Lung Cancer, in Black Participants

Semancik, C.; Zhao, N.; Koestler, D.; Boerwinkle, E.; Bressler, J.; Buchsbaum, R.; Kelsey, K. T.; Platz, E. A.; Michaud, D.

2024-05-09 epidemiology
10.1101/2024.05.09.24307118
Show abstract

Prior cohort studies assessing cancer risk based on immune cell subtype profiles have predominantly focused on White populations. This limitation obscures vital insights into how cancer risk varies across race. Immune cell subtype proportions were estimated using deconvolution based on leukocyte DNA methylation markers from blood samples collected at baseline on participants without cancer in the Atherosclerosis Risk in Communities (ARIC) Study. Over a mean of 17.5 years of follow-up, 668 incident cancers were diagnosed in 2,467 Black participants. Cox proportional hazards regression was used to examine immune cell subtype proportions and overall cancer incidence and site-specific incidence (lung, breast, and prostate cancers). Higher T regulatory cell proportions were associated with statistically significantly higher lung cancer risk (hazard ratio = 1.22, 95% confidence interval = 1.06-1.41 per percent increase). Increased memory B cell proportions were associated with significantly higher risk of prostate cancer (1.17, 1.04-1.33) and all cancers (1.13, 1.05-1.22). Increased CD8+ naive cell proportions were associated with significantly lower risk of all cancers in participants [≥]55 years (0.91, 0.83-0.98). Other immune cell subtypes did not display statistically significant associations with cancer risk. These results in Black participants align closely with prior findings in largely White populations. Findings from this study could help identify those at high cancer risk and outline risk stratifying to target patients for cancer screening, prevention, and other interventions. Further studies should assess these relationships in other cancer types, better elucidate the interplay of B cells in cancer risk, and identify biomarkers for personalized risk stratification.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
JNCI: Journal of the National Cancer Institute
based on 13 papers
Top 0.1%
8.3%
2
eLife
based on 262 papers
Top 2%
7.5%
3
Cancer Epidemiology, Biomarkers & Prevention
based on 14 papers
Top 0.1%
7.5%
4
Clinical Epigenetics
based on 21 papers
Top 0.1%
7.5%
5
International Journal of Cancer
based on 18 papers
Top 0.2%
6.4%
6
Nature Communications
based on 483 papers
Top 18%
4.5%
7
American Journal of Epidemiology
based on 54 papers
Top 2%
2.9%
8
Scientific Reports
based on 701 papers
Top 52%
2.9%
9
eBioMedicine
based on 82 papers
Top 0.7%
2.8%
50% of probability mass above
10
PLOS ONE
based on 1737 papers
Top 80%
2.8%
11
Cancers
based on 57 papers
Top 5%
2.4%
12
BMC Medicine
based on 155 papers
Top 10%
2.2%
13
Genome Medicine
based on 56 papers
Top 4%
1.8%
14
Clinical Infectious Diseases
based on 219 papers
Top 14%
1.6%
15
Nature Medicine
based on 88 papers
Top 11%
1.3%
16
Aging Cell
based on 21 papers
Top 2%
0.8%
17
Nature
based on 58 papers
Top 9%
0.8%
18
Human Molecular Genetics
based on 28 papers
Top 6%
0.7%
19
JAMA Network Open
based on 125 papers
Top 21%
0.7%
20
International Journal of Epidemiology
based on 65 papers
Top 10%
0.7%
21
Frontiers in Immunology
based on 140 papers
Top 8%
0.7%
22
Cell Reports
based on 25 papers
Top 3%
0.7%
23
British Journal of Cancer
based on 22 papers
Top 4%
0.7%
24
Human Genetics and Genomics Advances
based on 39 papers
Top 4%
0.7%
25
Science Translational Medicine
based on 40 papers
Top 6%
0.7%
26
iScience
based on 74 papers
Top 9%
0.7%
27
Journal of Clinical Investigation
based on 50 papers
Top 5%
0.7%
28
The Journal of Infectious Diseases
based on 137 papers
Top 12%
0.7%