Friday, March 25, 2016

On The Breast Cancer-Milk Connection: Part 1 [Review]

Galván-Salazar et al. recently published an association study examining the connection between meat and cow's milk consumption among women from Western Mexico:

Association of Milk and Meat Consumption with the Development of Breast Cancer in a Western Mexican Population.
Galván-Salazar HR1, Arreola-Cruz A2, Madrigal-Pérez D1, Soriano-Hernández AD1, Guzman-Esquivel J3, Montes-Galindo DA2, López-Flores RA3, Espinoza-Gomez F2, Rodríguez-Sanchez IP4, Newton-Sanchez OA2, Lara-Esqueda A2, Martinez-Fierro ML5, Briseño-Gomez XG6, Delgado-Enciso I1.
Breast Care (Basel). 2015 Dec;10(6):393-6. doi: 10.1159/000442230. Epub 2015 Dec 1.

"BACKGROUND: Breast cancer is a public health problem and it is the most common gynecologic neoplasia worldwide. The risk factors for its development are of both hereditary and environmental origin. Certain foods have been clearly associated with modifying the breast cancer risk. The aim of the present analysis was to evaluate the effects of cow's milk and meat consumption on the development of breast cancer in a population from Western Mexico (Colima).
MATERIAL AND METHODS:We studied 97 patients presenting with a histopathologic diagnosis of breast cancer and 104 control individuals who did not present with the disease (Breast Imaging Report and Data System (BI-RADS) 1-2). 80% of the population belonged to a low socioeconomic stratum. The main clinical characteristics were analyzed along with the lifetime consumption of meat and milk.
RESULTS: High milk consumption increased the breast cancer risk by 7.2 times (p = 0.008) whereas the consumption of meat was not significantly associated with the disease.
CONCLUSIONS: High consumption of cow's milk was a risk factor for the development of breast cancer. Further studies are needed to evaluate the effects of dietary patterns on the development of breast cancer in diverse populations with ethnic, cultural, and economic differences."

The abstract alone contains a plethora of further points that require further elucidation. In order to appraise these findings to the fullest extent possible, the context of both breast cancer and the literature itself must be established.

This entry is the first of a two part series examining the available data in the literature connecting milk consumption with breast cancer incidence.

Study Search Criteria
Search terms included "milk", "consumption", "breast", "cancer" and "carcinoma", with "milk" and "cancer" forming the inclusion criteria. PubMed was the selected database. All relevant entries were reviewed and included in these two entries.

Breast Cancer Pathophysiology
Breast tissue is comprised primarily of two distinct structures; glandular and stromal tissue. The former is made up of lobular units (milk-producing and ejecting structures) and lactiferous ducts (responsible for milk secretion transport), whereas the latter forms the supportive framework to hold the glandular tissue in place. [1] Breast cancer may arise in any cell line, but is more typical of the glandular tissue, where epithelial cells transform into carcinoma [1] (Diagram below) [2]:

Breast malignancies as observed in a tissue-specific manner (from 'Diagnosis and Management of Benign Breast Disease', see citation #2 below under 'References')

Milk, Breast Cancer & Association Studies

One of the earliest studies linking diet and cancer was undertaken by Gaskill et al. (1979), which found a positive correlation existed between dairy and fat consumption in adulthood among Americans. [3] A series of case-control studies emanating from Italy assessing for lifestyle modifiers for breast cancer also found a reportedly significant correlation with milk consumption after other variables were controlled. [4-6] An observational study in France conducted in 1986 again found a strong correlation between milk and alcohol consumption with breast cancer. [7] However, this series of consistent outcomes were seemingly broken by Iscovich et al.'s work from Argentina in 1989, which found the consumption of whole milk products was protective. [8]

Subsequent association data became increasingly specific in methodology. Mettlin et al. (1990) undertook a case-control study into overall cancer risk with a larger cohort than previous studies, while also taking milk type into consideration. Both whole and semi-skimmed (2%) milk both raised breast cancer risk. [9] A case-control interventional study aimed at reducing fat levels in middle-aged women (50-65 years) following breast cancer surgery found a statistically significant (p<0.01) correlation confirming dietary intervention worked. [10] However, the study did not contain longitudinal information regarding whether these dietary choices prevented a relapse in malignancy (Note: similar efforts can be found in the literature [22]). The prevailing thought of the times (as a likely consequence of outcomes determined by Mettlin et al. and other similar papers) was clearly that dairy fat was inextricably responsible for breast cancer development. [14]

The continued focus on breast cancer risk and fat was reflected in future work. Gaard et al. (1995) built upon earlier work, finding participants consuming ≥0.75L full-fat milk per week were statistically more likely to develop breast cancer than those that consumed ≤0.15L per week (RR=2.91). [11] Once more, later work (through Knekt et al. 1996) reported conflicted findings, where milk consumption was now found to correlate negatively with breast cancer risk (lowest consumption tertile set at RR=1, highest tertile found to be RR=0.43, p=3x10-3). [12] This particular paper, rather helpfully, addressed several prominent confounders, finding they did not modify the prior age-adjusted calculations to any significant degree. [12] More work from Northern Europe () found the same conclusion as Knekt et al. through a prospective longitudinal study spanning 25 years. [13]

With the advent of the 2000's came a series of papers which continued to throw previous conclusions into question. Hjartåker et al. (2001) determined that childhood consumption of milk resulted in a decreased incidence of breast cancer in young adulthood, but not later. [18] Additionally, no statistical difference was observed between full fat and semi-skimmed milk, with the overall pattern resulting in a decreased association between milk and breast cancer. [18]

The first attempt to collate data from previous studies was made in 2002, where data from eight prospective cohort studies were pooled together. [19] The authors concluded that, with the increased power afforded by the large sample size, there was no significant association between milk consumption and breast cancer. [19] A second review published in 2004 came to the same conclusion, but did reason that measurement error may have reduced positive correlations in studies which hadn't demonstrated an association. [22]

Further attempts to address the emerging discrepancies in the literature. In 2005, through a worldwide cohort examining nine differing time periods, Zhang & Kesteloot determined that milk did not contribute overall to the incidence of common cancers in the general public, but did conclude milk maintained a link to recent instances of breast cancer, even after non-milk fat consumption was corrected for. [23] Once more, later primary data went on to add to the litany of contradictory association studies, this time discovering that milk consumption negatively correlated with breast cancer incidence (OR = 0.87, further details in study) [24] or there was no association between milk consumption and pre- or post-menopausal breast cancer onset. [25]

Schematic depiction of recall bias in population sampling
(from, full attribution to the original authors)
At this stage, it is abundantly clear that the relationship between milk consumption and breast cancer is not immediately apparent through single association studies, even with sufficient statistical power.  As the primary data does not form any sort of consensus perspective, meta-analyses are required. A 1999 epidemiological paper (Männistö et al.) raised the possibility that some of the previous papers fell victim to recall bias, where participants unintentionally over- or under-report the consumption of certain foods to subscribe with existing ideals of health (see opposite). [16] A 2011 meta-analysis reviewing all available literature determined that total dairy fat intake and not milk specifically is responsible for the correlation with breast cancer. [26] A cohort study from Tanzania in 2013 found evidence that directly supported this meta-analysis, concluding that the ratio between polyunsaturated and saturated fats displayed a correlation with breast cancer. [27] These outcomes were, in part, confirmed in a similar study from Iran. [29]

A recent cohort study (Ji et al. 2015) defied the prior conventions by examining lactose intolerant individuals for cancer incidence rates. As a sub-population, lactose intolerant people are a worthy group to investigate, given the reduction in the potential for recall bias with respect to dairy consumption.  The standardised incident ratio of breast cancer in lactose intolerant individuals was found to be 0.79. [28]

The results from association studies have conflicted greatly over time, [17,20] but certain consistent themes have emerged irrespective of the absolute connection between milk consumption and breast cancer incidence. Although several older studies seemed to rule out the fat component in milk as being the proverbial glue that binds the occasional correlations together, the limitations in methodology prevented them from confirming whether the saturated fat content in milk specifically, or the sum dairy fat intake of the cohorts, had any role to play. Based on the latest findings, fat (specifically saturated) seems to be one (or at least one of) the culprits. As stated previously, there are some components of mammalian milk which should theoretically protect individuals from breast cancer (specifically vitamin D and calcium).

Given the lack of consistent outcomes in the epidemiological data, the following entry will examine the current biological data, addressing the established and emerging components of mammalian milk which may contribute to breast malignancy. To be continued.

This entry is based on current (as of March 2016) research data. It is by no means definitive. It is also intended an academic piece written purely for public consumption and does not constitute as medical advice. 

1. Normal Structure | [Last Accessed 23/03/2016]: 

2. Hindle, W, Mokbel, K, Glob. libr. women's med., (ISSN: 1756-2228) 2009; DOI 10.3843/GLOWM.10017

3. Gaskill SP, McGuire WL, Osborne CK, Stern MP. Breast cancer mortality and diet in the United States. Cancer Res. 1979 Sep;39(9):3628-37.

4. Talamini R, La Vecchia C, Decarli A, Franceschi S, Grattoni E, Grigoletto E, Liberati A, Tognoni G. Social factors, diet and breast cancer in a northern Italian population. Br J Cancer. 1984 Jun;49(6):723-9.

5. La Vecchia C, Pampallona S. Age at first birth, dietary practices and breast cancer mortality in various Italian regions. Oncology. 1986;43(1):1-6.

6. Decarli A, La Vecchia C. Environmental factors and cancer mortality in Italy: correlational exercise. Oncology. 1986;43(2):116-26.

7. Lê MG, Moulton LH, Hill C, Kramar A. Consumption of dairy produce and alcohol in a case-control study of breast cancer. J Natl Cancer Inst. 1986 Sep;77(3):633-6.

8. Iscovich JM, Iscovich RB, Howe G, Shiboski S, Kaldor JM. A case-control study of diet and breast cancer in Argentina. Int J Cancer. 1989 Nov 15;44(5):770-6.

9. Mettlin CJ, Schoenfeld ER, Natarajan N. Patterns of milk consumption and risk of cancer. Nutr Cancer. 1990;13(1-2):89-99.

10. Nordevang E, Callmer E, Marmur A, Holm LE. Dietary intervention in breast cancer patients: effects on food choice. Eur J Clin Nutr. 1992 Jun;46(6):387-96.

11. Gaard M1, Tretli S, Løken EB. Dietary fat and the risk of breast cancer: a prospective study of 25,892 Norwegian women. Int J Cancer. 1995 Sep 27;63(1):13-7.

12. P. Knekt, R. Järvinen, R. Seppänen, E. Pukkala, and A. Aromaa. Intake of dairy products and the risk of breast cancer. Br J Cancer. 1996 Mar; 73(5): 687–691.

13. Järvinen R, Knekt P, Seppänen R, Teppo L. Diet and breast cancer risk in a cohort of Finnish women. Cancer Lett. 1997 Mar 19;114(1-2):251-3.

14. Outwater JL, Nicholson A, Barnard N. Dairy products and breast cancer: the IGF-I, estrogen, and bGH hypothesis. Med Hypotheses. 1997 Jun;48(6):453-61.

15. Webb PM, Bain CJ, Purdie DM, Harvey PW, Green A. Milk consumption, galactose metabolism and ovarian cancer (Australia). Cancer Causes Control. 1998 Dec;9(6):637-44.

16. Männistö S, Pietinen P, Virtanen M, Kataja V, Uusitupa M. Diet and the risk of breast cancer in a case-control study: does the threat of disease have an influence on recall bias? J Clin Epidemiol. 1999 May;52(5):429-39.

17. Zava DT, Blen M, Duwe G. Estrogenic activity of natural and synthetic estrogens in human breast cancer cells in culture. Environ Health Perspect. 1997 Apr;105 Suppl 3:637-45.

18. Hjartåker A, Laake P, Lund E. Childhood and adult milk consumption and risk of premenopausal breast cancer in a cohort of 48,844 women - the Norwegian women and cancer study. Int J Cancer. 2001 Sep;93(6):888-93.

19. Missmer SA, Smith-Warner SA, Spiegelman D, Yaun SS, Adami HO, Beeson WL. Meat and dairy food consumption and breast cancer: a pooled analysis of cohort studies. Int J Epidemiol. 2002 Feb;31(1):78-85.

20. Bradlow HL, Sepkovic DW. Diet and breast cancer. Ann N Y Acad Sci. 2002 Jun;963:247-67.

21. Li XM1, Ganmaa D, Sato A. The experience of Japan as a clue to the etiology of breast and ovarian cancers: relationship between death from both malignancies and dietary practices. Med Hypotheses. 2003 Feb;60(2):268-75.

22. Shaharudin SH, Sulaiman S, Shahril MR, Emran NA, Akmal SN. Dietary changes among breast cancer patients in Malaysia. Cancer Nurs. 2013 Mar-Apr;36(2):131-8. doi: 10.1097/NCC.0b013e31824062d1.

23. Zhang J, Kesteloot H. Milk consumption in relation to incidence of prostate, breast, colon, and rectal cancers: is there an independent effect? Nutr Cancer. 2005;53(1):65-72.

24. Gallus S, Bravi F, Talamini R, Negri E, Montella M, Ramazzotti V. Milk, dairy products and cancer risk (Italy). Cancer Causes Control. 2006 May;17(4):429-37.

25. Hjartåker A, Thoresen M, Engeset D, Lund E. Dairy consumption and calcium intake and risk of breast cancer in a prospective cohort: the Norwegian Women and Cancer study. Cancer Causes Control. 2010 Nov;21(11):1875-85. doi: 10.1007/s10552-010-9615-5. Epub 2010 Jul 25.

26. Dong JY, Zhang L, He K, Qin LQ. Dairy consumption and risk of breast cancer: a meta-analysis of prospective cohort studies. Breast Cancer Res Treat. 2011 May;127(1):23-31. doi: 10.1007/s10549-011-1467-5. Epub 2011 Mar 27.

27. Jordan I, Hebestreit A, Swai B, Krawinkel MB. Dietary patterns and breast cancer risk among women in northern Tanzania: a case-control study. Eur J Nutr. 2013 Apr;52(3):905-15. doi: 10.1007/s00394-012-0398-1. Epub 2012 Jun 23.

28. Ji J1, Sundquist J2, Sundquist K2. Lactose intolerance and risk of lung, breast and ovarian cancers: aetiological clues from a population-based study in Sweden. Br J Cancer. 2015 Jan 6;112(1):149-52. doi: 10.1038/bjc.2014.544. Epub 2014 Oct 14.

29. Mobarakeh ZS, Mirzaei K, Hatmi N, Ebrahimi M, Dabiran S, Sotoudeh G. Dietary habits contributing to breast cancer risk among Iranian women. Asian Pac J Cancer Prev. 2014;15(21):9543-7.

Saturday, March 19, 2016

Identifying Bias in Cohorts: IBD and Life Stage Effect [Review]

A very interesting paper published barely one week ago investigating the potential for bias exertion in population genetics cohorts:

Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages.
Peterman W1, Brocato ER2, Semlitsch RD2, Eggert LS2.
PeerJ. 2016 Mar 14;4:e1813. doi: 10.7717/peerj.1813. eCollection 2016.

"In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (F ST and D C ) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using D C , the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis."

How relevant is the above to human population genetics? Quite, for two reasons:
  1. Per the accepted phenomenon which props the IBD model, the study does give a unique angle with respect to sampling methods. The difference in IBD status as determined by life stage, alongside statistical demonstration of insignificance once only A. maculatum larvae and embryos were considered, confirms social mobility plays a role in obscuring intra-species IBD measurements. This is clearly mitigated in human settlements with extreme geographical isolation.
  2. More microsatellite markers are usually better - Genetic genealogists or researchers familiar with Y-chromosomal analyses are already aware of this mantra. Not a surprise to see the authors concluded their statistical power increased when the maximum number of markers were employed.
The abstract, rather unhelpfully, does not reveal the outcomes of the sibling-pair variation to their experimentation. 

A full read of the paper at some point should hopefully address the above, as well as the raw data produced through the statistical calculations.