Conceived and designed the experiments: AT CF RT MNG. Performed the experiments: AA AO MP BHK HL ACormio VC FG VG. Analyzed the data: AA AO VB CS LS. Contributed reagents/materials/analysis tools: AT CF RT. Wrote the paper: AA AO UAP ACeriello OS AT. Performed the collection of clinical/biometric data, blood and DNA samples: RT AS MM ARB MB IT.
The authors have declared that no competing interests exist.
Mitochondrial dysfunction has been implicated in rare and common forms of type 2 diabetes (T2DM). Additionally, rare mitochondrial DNA (mtDNA) mutations have been shown to be causal for T2DM pathogenesis. So far, many studies have investigated the possibility that mtDNA variation might affect the risk of T2DM, however, when found, haplogroup association has been rarely replicated, even in related populations, possibly due to an inadequate level of haplogroup resolution. Effects of mtDNA variation on diabetes complications have also been proposed. However, additional studies evaluating the mitochondrial role on both T2DM and related complications are badly needed. To test the hypothesis of a mitochondrial genome effect on diabetes and its complications, we genotyped the mtDNAs of 466 T2DM patients and 438 controls from a regional population of central Italy (Marche). Based on the most updated mtDNA phylogeny, all 904 samples were classified into 57 different mitochondrial sub-haplogroups, thus reaching an unprecedented level of resolution. We then evaluated whether the susceptibility of developing T2DM or its complications differed among the identified haplogroups, considering also the potential effects of phenotypical and clinical variables. MtDNA backgrounds, even when based on a refined haplogroup classification, do not appear to play a role in developing T2DM despite a possible protective effect for the common European haplogroup H1, which harbors the G3010A transition in the MTRNR2 gene. In contrast, our data indicate that different mitochondrial haplogroups are significantly associated with an increased risk of specific diabetes complications: H (the most frequent European haplogroup) with retinopathy, H3 with neuropathy, U3 with nephropathy, and V with renal failure.
The etiology of type 2, or non-insulin-dependent, diabetes mellitus (T2DM), the most common metabolic disease in the Western hemisphere, is the result of an interaction of environmental factors with a combination of genetic variants, most of which are still unknown. Case-control studies can be used to predict and quantify the association of genetic factors and lifestyle with some common diseases, thus contributing to the body of knowledge of primary prevention for these conditions. Different genome-wide association studies have led to recent discoveries of novel diabetes-related nuclear loci
Obviously, the possibility of obtaining false positive/negative results is greatly decreased when patients and controls come from the same population and/or geographic area where the genetic background should be more homogenous. This is particularly true when association studies involve a genetic system such as the maternally transmitted mitochondrial DNA (mtDNA), whose worldwide “natural” sequence variation is geographically and ethnically differentiated. MtDNA haplotypes and haplogroups (groups of mtDNA haplotypes sharing the same mutational motifs by descent from a common female ancestor) are extremely common in one continent or even a single geographic area/population group, but completely absent in all others
Mitochondrial involvement in the pathogenesis of major common metabolic disorders, including T2DM, stems from the observation of dysfunctions in the mitochondrial energy production machinery (OXPHOS) of many patients
A second general area of investigation concerns the role of mtDNA variants or haplogroups in modulating susceptibility to develop diabetes complications, usually classified into macrovascular (cardiovascular disease, cerebrovascular accidents, and peripheral vascular disease) and microvascular complications (diabetic nephropathy, neuropathy, and retinopathy)
In this study, to evaluate the role of mtDNA backgrounds, not only in T2DM as a whole but also in its associated complications, we have genotyped, at an extremely high level of phylogenetic resolution, the mitochondrial genome of a large number of subjects (466 T2DM patients and 438 controls) from the Marche region of central Italy.
Before determining the extent and nature of mtDNA variation in control and diabetic subjects from the Marche region, we investigated the effects of a large number of phenotypical and clinical variables on the risk of T2DM. Some of the traits evaluated in the 904 subjects are shown in
All samples |
Males |
Females |
|||||||||
Variables | Patients (N = 466) | Controls (N = 438) |
|
Patients (N = 257) | Controls (N = 176) |
|
Patients (N = 209) | Controls (N = 262) |
|
N analyzed (Males;Females) | |
|
Age [years] | 65.84±8.19 | 59.96±9.97 | <0.0001 | 65.09±8.55 | 59.34±9.40 | <0.0001 | 66.76±7.64 | 60.38±10.32 | <0.0001 | 904 (433;471) |
Sex [M/F (%)] | 257/209 (55.15%/44.85%) | 176/262 (40.18%/59.82%) | <0.0001 | ||||||||
BMI [Kg/m2] | 28.76±4.62 | 27.14±4.46 | <0.0001 | 28.24±4.15 | 27.29±3.51 | 0.0107 | 29.40±5.07 | 27.04±5.00 | <0.0001 | 902 (432;470) | |
Obesity |
152 (32.69%) | 96 (21.97%) | 0.0003 | 71 (27.73%) | 35 (19.89%) | 0.0696 | 81 (38.76%) | 61 (23.37%) | 0.0004 | 902 (432;470) | |
Smokers (%) | 124 (28.64%) | 76 (16.14%) | 0.0010 | 92 (35.80%) | 32 (18.18%) | <0.0001 | 36 (17.22%) | 40 (15.27%) | 0.6147 | 904 (433;471) | |
Metabolic Syndrome |
267 (57.42%) | 56 (12.90%) | <0.0001 | 114 (44.53%) | 16 (9.25%) | <0.0001 | 153 (73.21%) | 40 (15.33%) | <0.0001 | 899 (429;470) | |
Insulin Resistance |
190 (40.77%) | 54 (12.47%) | <0.0001 | 97 (37.74%) | 26 (15.12%) | <0.0001 | 93 (44.50%) | 28 (10.73%) | <0.0001 | 899 (429;470) | |
Fibrinogen [mg/dL] | 303.50±79.49 | 295.29±71.76 | 0.1590 | 294.04±77.85 | 281.95±78.17 | 0.2012 | 315.36±80.11 | 302.89±66.90 | 0.1064 | 706 (342;364) | |
C-reactive protein [mg/L] | 4.55±7.01 | 3.43±7.37 | 0.0200 | 4.20±6.74 | 3.62±10.45 | 0.5179 | 4.97±7.31 | 3.30±4.17 | 0.0035 | 901 (431;470) | |
HbA1c [%] | 7.43±1.25 | 5.67±0.40 | <0.0001 | 7.37±1.28 | 5.59±0.36 | <0.0001 | 7.51±1.20 | 5.72±0.42 | <0.0001 | 904 (433;471) | |
HDL [mg/dL] | 52.75±14.85 | 58.32±15.17 | <0.0001 | 49.44±12.10 | 51.77±13.50 | 0.0682 | 56.82±16.80 | 62.64±14.68 | <0.0001 | 901 (430;471) | |
Triglycerides | 138.38±93.16 | 103.28±68.45 | <0.0001 | 136.12±101.92 | 119.09±88.70 | 0.0674 | 141.16±81.26 | 92.85±48.34 | <0.0001 | 899 (429;470) | |
Hypertension (%) | 293 (62.88%) | 137 (31.35%) | <0.0001 | 155 (60.31%) | 40 (22.86%) | <0.0001 | 138 (66.03%) | 97 (37.02%) | <0.0001 | 903 (432;471) | |
|
Retinopathy (%) | 132 (28.33%) | ··· | ··· | 69 (26.85%) | ··· | ··· | 63 (30.14%) | ··· | ··· | 904 (433;471) |
Somatic Neuropathy (%) | 94 (20.17%) | ··· | ··· | 64 (24.90%) | ··· | ··· | 30 (14.35%) | ··· | ··· | 904 (433;471) | |
Cardiac Ischemia (%) | 81 (8.96%) | ··· | ··· | 50 (19.46%) | ··· | ··· | 31 (14.83%) | ··· | ··· | 904 (433;471) | |
Nephropathy (%) | 64 (13.73%) | ··· | ··· | 45 (17.51%) | ··· | – | 19 (9.09%) | ··· | ··· | 904 (433;471) | |
Peripheral Artery Occlusive Disease (PAOD)(%) | 30 (3.2%) | ··· | ··· | 17 (6.61%) | ··· | ··· | 13 (6.22%) | ··· | ··· | 904 (433;471) | |
Renal Failure (%) | 20 (2.21%) | ··· | ··· | 15 (5.84%) | ··· | ··· | 5 (2.39%) | ··· | ··· | 904 (433;471) | |
|
HOMA-IR | 2.99±3.52 | 1.59±1.55 | <0.0001 | 3.14±4.22 | 1.74±1.78 | <0.0001 | 2.81±2.39 | 1.49±1.36 | <0.0001 | 904 (433;471) |
Values are means ± standard deviation (or absolute number and percentages).
BMI ≥30.
Diagnosed according to the criteria proposed by the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III).
HOMA-IR >2.5.
All 904 mtDNAs were genotyped and assigned to 57 different mtDNA haplogroups and sub-haplogroups (
All samples | Males | Females | ||||||
Haplogroup |
Patients (%) | Controls (%) | Patients (%) | Controls (%) | Patients (%) | Controls (%) | Total (%) | |
|
|
|
|
|
|
|
||
|
161 (34.55%) | 181 (41.34%) | 90 (35.01%) | 66 (37.50%) | 71 (33.96%) | 115 (43.89%) | 342 (37.83%) | |
H* | 77 (16.52%) | 72 (16.44%) | 43 (16.73%) | 29 (16.48%) | 34 (16.27%) | 43 (16.41%) | 149 (16.48%) | |
H1 | 44 (9.44%) | 69 (15.75%) | 23 (8.95%) | 23 (13.07%) | 21 (10.05%) | 46 (17.56%) | 113 (12.50%) | |
H3 | 10 (2.15%) | 13 (2.97%) | 6 (2.33%) | 8 (4.55%) | 4 (1.91%) | 5 (1.91%) | 23 (2.54%) | |
H5 | 16 (3.43%) | 17 (3.88%) | 11 (4.28%) | 3 (1.70%) | 5 (2.39%) | 14 (5.34%) | 33 (3.65%) | |
H6 | 10 (2.15%) | 7 (1.60%) | 5 (1.95%) | 2 (1.14%) | 5 (2.39%) | 5 (1.91%) | 17 (1.88%) | |
H8 | … | 2 (0.46%) | … | 1 (0.57%) | … | 1 (0.38%) | 2 (0.22%) | |
H9 | 4 (0.86%) | 1 (0.23%) | 2 (0.78%) | … | 2 (0.96%) | 1 (0.38%) | 5 (0.55%) | |
|
37 (7.94%) | 29 (6.62%) | 25 (9.73%) | 13 (7.39%) | 12 (5.74%) | 16 (6.11%) | 66 (7.30%) | |
HV* | 15 (3.22%) | 17 (3.88%) | 8 (3.11%) | 9 (5.11%) | 7 (3.35%) | 8 (3.05%) | 32 (3.54%) | |
HV0 | 4 (0.86%) | 1 (0.23%) | 3 (1.17%) | … | 1 (0.48%) | 1 (0.38%) | 5 (0.55%) | |
V | 18 (3.86%) | 11 (2.51%) | 14 (5.45%) | 4 (2.27%) | 4 (1.91%) | 7 (2.67%) | 29 (3.21%) | |
|
6 (1.29%) | … | 3 (1.17%) | … | 3 (1.44%) | … | 6 (0.66%) | |
R0a | 6 (1.29%) | … | 3 (1.17%) | … | 3 (1.44%) | … | 6 (0.66%) | |
|
33 (7.08%) | 37 (8.45%) | 21 (8.17%) | 19 (10.80%) | 12 (5.74%) | 18 (6.87%) | 70 (7.75%) | |
J1 | 27 (5.79%) | 31 (7.08%) | 18 (7.00%) | 16 (9.09%) | 9 (4.31%) | 15 (5.73%) | 58 (6.42%) | |
J2 | 6 (1.29%) | 6 (1.37%) | 3 (1.17%) | 3 (1.70%) | 3 (1.44%) | 3 (1.15%) | 12 (1.33%) | |
|
71 (15.24%) | 57 (13.01%) | 37 (14.39%) | 23 (13.07%) | 34 (16.27%) | 34 (12.98%) | 128 (14.16%) | |
T1 | 12 (2.58%) | 11 (2.51%) | 7 (2.72%) | 3 (1.70%) | 5 (2.39%) | 8 (3.05%) | 23 (2.54%) | |
T2 | 59 (12.66%) | 46 (10.50%) | 30 (11.67%) | 20 (11.36%) | 29 (13.88%) | 26 (9.92%) | 105 (11.62%) | |
|
||||||||
U | 80 (17.17%) | 65 (14.84%) | 48 (18.68%) | 25 (14.20%) | 32 (15.31%) | 40 (15.26%) | 145 (16.04%) | |
U1 | 3 (0.64%) | 4 (0.91%) | 3 (1.17%) | 2 (1.14%) | … | 2 (0.76%) | 7 (0.77%) | |
U2 | 1 (0.21%) | 1 (0.23%) | 1 (0.39%) | … | … | 1 (0.38%) | 2 (0.22%) | |
U3 | 13 (2.79%) | 11 (2.51%) | 10 (3.89%) | 4 (2.27%) | 3 (1.44%) | 7 (2.67%) | 24 (2.65%) | |
U4 | 12 (2.58%) | 8 (1.83%) | 6 (2.33%) | 5 (2.84%) | 6 (2.87%) | 3 (1.15%) | 20 (2.21%) | |
U5 | 39 (8.37%) | 34 (7.76%) | 21 (8.17%) | 10 (5.68%) | 18 (8.61%) | 24 (9.16%) | 73 (8.08%) | |
U6 | 2 (0.43%) | 1 (0.23%) | … | 1 (0.57%) | 2 (0.96%) | … | 3 (0.33%) | |
U7 | 4 (0.86%) | 2 (0.46%) | 2 (0.78%) | 1 (0.57%) | 2 (0.96%) | 1 (0.38%) | 6 (0.66%) | |
U8 | 5 (1.07%) | 4 (0.91%) | 4 (1.56%) | 2 (1.14%) | 1 (0.48%) | 2 (0.76%) | 9 (1.00%) | |
U9 | 1 (0.21%) | … | 1 (0.39%) | … | … | … | 1 (0.11%) | |
K | 31 (6.65%) | 24 (5.48%) | 12 (4.67%) | 15 (8.52%) | 19 (9.09%) | 9 (3.44%) | 55 (6.08%) | |
K1 | 30 (6.44%) | 22 (5.02%) | 12 (4.67%) | 13 (7.39%) | 18 (8.61%) | 9 (3.44%) | 52 (5.75%) | |
K2 | 1 (0.21%) | 2 (0.46%) | … | 2 (1.14%) | 1 (0.48%) | … | 3 (0.33%) | |
|
17 (3.65%) | 9 (2.05%) | 9 (3.50%) | 1 (0.57%) | 8 (3.83%) | 8 (3.05%) | 26 (2.88%) | |
N1 | 9 (1.93%) | 6 (1.37%) | 6 (2.33%) | 1 (0.57%) | 3 (1.44%) | 5 (1.91%) | 15 (1.66%) | |
I | 8 (1.72%) | 3 (0.68%) | 3 (1.17%) | … | 5 (2.39%) | 3 (1.15%) | 11 (1.22%) | |
|
6 (1.29%) | 8 (1.83%) | 3 (1.17%) | 4 (2.27%) | 3 (1.44%) | 4 (1.53%) | 14 (1.55%) | |
W | 6 (1.29%) | 8 (1.83%) | 3 (1.17%) | 4 (2.27%) | 3 (1.44%) | 4 (1.53%) | 14 (1.55%) | |
|
13 (2.79%) | 15 (3.42%) | 4 (1.56%) | 5 (2.84%) | 9 (4.31%) | 10 (3.82%) | 28 (3.10%) | |
X2 | 13 (2.79%) | 15 (3.42%) | 4 (1.56%) | 5 (2.84%) | 9 (4.31%) | 10 (3.82%) | 28 (3.10%) | |
|
10 (2.15%) | 8 (1.82%) | 5 (1.95%) | 3 (1.70%) | 5 (2.39%) | 5 (1.91%) | 18 (1.99%) | |
D4 | 5 (1.07%) | 3 (0.68%) | 4 (1.56%) | 2 (1.14%) | 1 (0.48%) | 1 (0.38%) | 8 (0.88%) | |
M1 | 5 (1.07%) | 5 (1.14%) | 1 (0.39%) | 1 (0.57%) | 4 (1.91%) | 4 (1.53%) | 10 (1.11%) | |
|
1 (0.21%) | 5 (1.14%) | … | 2 (1.14%) | 1 (0.48%) | 3 (1.15%) | 6 (0.66%) | |
L1b | … | 1 (0.23%) | … | … | … | 1 (0.38%) | 1 (0.11%) | |
L3 | 1 (0.21%) | 4 (0.91%) | … | 2 (1.14%) | 1 (0.48%) | 2 (0.76%) | 5 (0.55%) |
H* is a paragroup that encompasses all H mtDNAs that did not belong to any of the tested subclades of H.
Without H.
When we compared haplogroup distributions of T2DM cases and controls (
The schematic classification of the R0a sub-clades is based on Černý et al.
Many studies have evaluated mtDNA variation in T2DM patients. However, only a few studies have tested mtDNA haplogroups for association with diabetes complications. In an attempt to investigate a potential role of mtDNA backgrounds in complications rather than in T2DM as a whole, we evaluated this issue in our population sample.
All Samples |
Males | Females | |||||||
No complications | At least one complication | At least two complications | No complications | At least one complication | At least two complications | No complications | At least one complication | At least two complications | |
|
|
|
|
|
|
|
|
|
|
|
68 (30.49%) | 93 (38.27%) | 49 (44.95%) | 34 (30.64%) | 56 (38.38%) | 29 (42.03%) | 34 (30.36%) | 37 (38.16%) | 20 (50.00%) |
|
34 (15.25%) | 43 (17.70%) | 26 (23.85%) | 18 (16.22%) | 25 (17.12%) | 14 (20.29%) | 16 (14.29%) | 18 (18.56%) | 12 (30.00%) |
|
19 (8.52%) | 25 (10.29%) | 12 (11.01%) | 9 (8.11%) | 14 (9.59%) | 8 (11.59%) | 10 (8.93%) | 11 (11.34%) | 4 (10.00%) |
|
1 (0.45%) | 9 (3.70%) | 6 (5.50%) | ··· | 6 (4.11%) | 3 (4.35%) | 1 (0.89%) | 3 (3.09%) | 3 (7.50%) |
|
8 (3.59%) | 8 (3.29%) | 3 (2.75%) | 6 (5.41%) | 5 (3.42%) | 3 (4.35%) | 2 (1.79%) | 3 (3.09%) | ··· |
|
4 (1.79%) | 6 (2.47%) | 2 (1.83%) | 1 (0.90%) | 4 (2.74%) | 1 (1.45%) | 3 (2.68%) | 2 (2.06%) | 1 (2.50%) |
|
2 (0.90%) | 2 (0.82%) | ··· | ··· | 2 (1.37%) | ··· | 2 (1.79%) | ··· | ··· |
|
20 (8.97%) | 17 (7.00%) | 8 (7.34%) | 11 (9.91%) | 14 (9.59%) | 8 (11.59%) | 9 (8.04%) | 3 (3.09%) | ··· |
|
10 (4.48%) | 5 (2.06%) | ··· | 5 (4.50%) | 3 (2.05%) | ··· | 5 (4.46%) | 2 (2.06%) | ··· |
|
2 (0.90%) | 2 (0.82%) | 1 (0.92%) | 2 (1.80%) | 1 (0.68%) | 1 (1.45%) | ··· | 1 (1.03%) | ··· |
|
8 (3.59%) | 10 (4.12%) | 7 (6.42%) | 4 (3.60%) | 10 (6.85%) | 7 (10.14%) | 4 (3.57%) | ··· | ··· |
|
2 (0.90%) | 4 (1.65%) | 1 (0.92%) | ··· | 3 (2.05%) | 1 (1.45%) | 2 (1.79%) | 1 (1.03%) | ··· |
|
2 (0.90%) | 4 (1.65%) | 1 (0.92%) | ··· | 3 (2.05%) | 1 (1.45%) | 2 (1.79%) | 1 (1.03%) | ··· |
|
17 (7.62%) | 16 (6.58%) | 5 (4.59%) | 10 (9.01%) | 11 (7.53%) | 4 (5.80%) | 7 (6.25%) | 5 (5.15%) | 1 (2.50%) |
|
13 (5.83%) | 14 (5.76%) | 5 (4.59%) | 7 (6.31%) | 11 (7.53%) | 4 (5.80%) | 6 (5.36%) | 3 (3.09%) | 1 (2.50%) |
|
4 (1.79%) | 2 (0.82%) | ··· | 3 (2.70%) | ··· | ··· | 1 (0.89%) | 2 (2.06%) | ··· |
|
41 (18.39%) | 30 (12.35%) | 13 (11.93%) | 22 (19.82%) | 15 (10.27%) | 7 (10.14%) | 19 (16.96%) | 15 (15.46%) | 6 (15.00%) |
|
6 (2.69%) | 6 (2.47%) | 3 (2.75%) | 2 (1.80%) | 5 (3.42%) | 2 (2.90%) | 4 (3.57%) | 1 (1.03%) | 1 (2.50%) |
|
35 (15.70%) | 24 (9.88%) | 10 (9.17%) | 20 (18.02%) | 10 (6.85%) | 5 (7.25%) | 15 (13.39%) | 14 (14.43%) | 5 (12.50%) |
|
|||||||||
|
36 (16.14%) | 44 (18.10%) | 19 (17.43%) | 18 (16.22%) | 30 (20.55%) | 12 (17.39%) | 18 (16.06%) | 14 (14.43%) | 7 (17.50%) |
|
1 (0.45%) | 2 (0.82%) | 1 (0.92%) | 1 (0.90%) | 2 (1.37%) | 1 (1.45%) | ··· | ··· | ··· |
|
··· | 1 (0.41%) | ··· | ··· | 1 (0.68%) | ··· | ··· | ··· | ··· |
|
6 (2.69%) | 7 (2.88%) | 6 (5.50%) | 5 (4.50%) | 5 (3.42%) | 4 (5.80%) | 1 (0.89%) | 2 (2.06%) | 2 (5.00%) |
|
7 (3.14%) | 5 (2.06%) | 1 (0.92%) | 2 (1.80%) | 4 (2.74%) | ··· | 5 (4.46%) | 1 (1.03%) | 1 (2.50%) |
|
19 (8.52%) | 20 (8.23%) | 8 (7.34%) | 8 (7.21%) | 13 (8.90%) | 5 (7.25%) | 11 (9.82%) | 7 (7.22%) | 3 (7.50%) |
|
··· | 2 (0.82%) | ··· | ··· | ··· | ··· | ··· | 2 (2.06%) | ··· |
|
2 (0.90%) | 2 (0.82%) | ··· | 1 (0.90%) | 1 (0.68%) | ··· | 1 (0.89%) | 1 (1.03%) | ··· |
|
1 (0.45%) | 4 (1.65%) | 2 (1.83%) | 1 (0.90%) | 3 (2.05%) | 1 (1.45%) | ··· | 1 (1.03%) | 1 (2.50%) |
|
··· | 1 (0.41%) | 1 (0.92%) | ··· | 1 (0.68%) | 1 (1.45%) | ··· | ··· | ··· |
|
12 (5.38%) | 19 (7.82%) | 4 (3.67%) | 2 (1.80%) | 10 (6.85%) | 4 (5.80%) | 10 (8.93%) | 9 (9.28%) | ··· |
|
12 (5.38%) | 18 (7.41%) | 4 (3.67%) | 2 (1.80%) | 10 (6.85%) | 4 (5.80%) | 10 (8.93%) | 8 (8.25%) | ··· |
|
1 (0.41%) | ··· | ··· | ··· | ··· | ··· | 1 (1.03%) | ··· | |
|
7 (3.14%) | 10 (4.12%) | 5 (4.59%) | 5 (4.50%) | 4 (2.74%) | 1 (1.45%) | 2 (1.79%) | 6 (6.19%) | 4 (10.00%) |
|
4 (1.79%) | 5 (2.06%) | 2 (1.83%) | 4 (3.60%) | 2 (1.37%) | ··· | ··· | 3 (3.09%) | 2 (5.00%) |
|
3 (1.35%) | 5 (2.06%) | 3 (2.75%) | 1 (0.90%) | 2 (1.37%) | 1 (1.45%) | 2 (1.79%) | 3 (3.09%) | 2 (5.00%) |
|
4 (1.79%) | 2 (0.82%) | 1 (0.92%) | 2 (1.80%) | 1 (0.68%) | 1 (1.45%) | 2 (1.79%) | 1 (1.03%) | ··· |
|
4 (1.79%) | 2 (0.82%) | 1 (0.92%) | 2 (1.80%) | 1 (0.68%) | 1 (1.45%) | 2 (1.79%) | 1 (1.03%) | ··· |
|
8 (3.59%) | 5 (2.06%) | 2 (1.83%) | 3 (2.70%) | 1 (0.68%) | 1 (1.45%) | 5 (4.46%) | 4 (4.12%) | 1 (2.50%) |
|
8 (3.59%) | 5 (2.06%) | 2 (1.83%) | 3 (2.70%) | 1 (0.68%) | 1 (1.45%) | 5 (4.46%) | 4 (4.12%) | 1 (2.50%) |
|
7 (3.14%) | 3 (1.23%) | 2 (1.83%) | 4 (3.60%) | 1 (0.68%) | 1 (1.45%) | 3 (2.68%) | 2 (2.06%) | 1 (2.50%) |
|
4 (1.79%) | 1 (0.41%) | 1 (0.92%) | 3 (2.70%) | 1 (0.68%) | 1 (1.45%) | 1 (0.89%) | … | ··· |
|
3 (1.35%) | 2 (0.82%) | 1 (0.92%) | 1 (0.90%) | ··· | ··· | 2 (1.79%) | 2 (2.06%) | 1 (2.50%) |
|
1 (0.45%) | ··· | ··· | ··· | ··· | ··· | 1 (0.89%) | ··· | ··· |
|
··· | ··· | ··· | ··· | ··· | ··· | ··· | ··· | ··· |
|
1 (0.45%) | ··· | ··· | ··· | ··· | ··· | 1 (0.89%) | ··· | ··· |
Haplogroup frequencies in males and females are reported for congruency with previous tables. However, gender was not considered in statistical analyses dealing with complications.
Modeled Outcome | Haplogroup |
|
O.R. |
95% C.I. |
One complication ( |
||||
H3 | 0.0427 | 8.5385 | 1.0730–67.9460 | |
Two complications ( |
||||
H* | 0.0083 | 2.0682 | 1.2055–3.5481 | |
H3 | 0.0044 | 6.5625 | 1.7993–23.9349 | |
U3 | 0.0211 | 3.7500 | 1.2190–11.5361 | |
V | 0.0418 | 2.7841 | 1.0389–7.4610 |
Odd ratio.
Confidence interval.
Modeled Outcome |
Characteristics |
|
O.R. | 95% C.I. |
H3 subjects ( |
||||
Neuropathy | 0.0012 | 9.6389 | 2.4411–38.0594 | |
H |
||||
Retinopathy | 0.0014 | 2.0075 | 1.3080–3.0812 | |
HDL | 0.0259 | 0.9836 | 0.9694–0.9980 | |
U3 subjects ( |
||||
Nephropathy | 0.0154 | 4.1518 | 1.3118–13.1401 | |
V subjects ( |
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Renal Failure | 0.0103 | 5.8429 | 1.5159–22.5206 |
The candidate haplogroup was analyzed in relation to the patients' traits and complications reported in
H here represents the entire clade, thus including H*, H1, H3, H5, H6 and H9.
Finally, U3 and V subjects showed an increased occurrence of nephropathy (OR = 4.1518, 95% CI: 1.3118–13.1401,
In order to compute confidence bounds around the predictions, we tested the significant haplogroups trough a decision tree analysis. Actually, all the reported associations were supported (
As a first step in this study, we examined the relationships between T2DM and a wide range of mtDNA haplogroups and sub-haplogroups in a large-scale association study carried out on an Italian regional population. A reduced susceptibility to diabetes was possibly detected only for the H1 mtDNA background (9.4% and 15.8% in patients and controls, respectively). This H sub-branch is common in Western Europe (∼22% in the Iberian Peninsula, ∼13.7% in France and ∼15.3% in Scandinavia) and North Africa (average frequency of ∼16%)
The distinguishing mutational motifs for the haplogroups shown in the tree are reported on the branches and they are transitions unless a base is explicitly indicated. The position of the rCRS
Similar to haplogroup H1, the rare R0a2 branch (
Unfortunately, neither the association with haplogroup H1 nor that with haplogroup R0a was statistically supported. In fact, the R0a mtDNAs were too few to be included in the logistic regression, and H1 did not reach the established level of significance after the Bonferroni correction (
In contrast, when we evaluated the potential role of mtDNA backgrounds in complications rather than in T2DM as a whole, we were able to build a very significant logistic model (
The excess of U3 mtDNAs among nephropathic subjects (7.8%
As for haplogroup V, it was found to be associated with renal failure (15.0% in cases
Overall, we observed that most of the candidate branches in the mtDNA tree are characterized by mutations in the MTRNR2 gene and amino acid changes affecting cytochrome b and subunits of the respiratory enzyme complex I (
In conclusion, our data appear to indicate that mitochondrial backgrounds do not play a significant role in causing the onset of type 2 diabetes, despite indications of a protective effect for haplogroup H1 – possibly due to the G3010A transition in the MTRNR2 gene. As H1 is common in Western Europe, such a possibility might be further evaluated by assaying diabetic cohorts (and matched controls) of other European populations (see below). In contrast, we found significant associations between some European mtDNA haplogroups and typical diabetes complications. We cannot exclude that these associations might be influenced by nuclear genomic backgrounds and genetic substructure of the analyzed population, or biased by the reduced statistical power due to the decreased sample size of subgroups (patients with T2DM complications ascribed to different haplogroups)
Haplogroup |
Power (%) |
||
T2DM Patients/Controls | At least one complication/No complications | At least two complications/One or no complications | |
|
|
6.12 | 5.28 |
|
6.60 |
|
|
|
4.99 | 4.49 | 4.79 |
|
6.07 | 5.43 | 4.53 |
|
4.42 | 5.07 |
|
|
4.37 | 11.98 | 17.81 |
|
10.15 | 4.67 |
|
|
|
n.d. | n.d. |
|
6.78 | 5.06 | 8.08 |
|
4.40 | 4.44 | 4.44 |
|
8.62 | 19.82 | 8.60 |
|
4.67 | 20.66 |
|
|
4.79 | 4.42 | 4.91 |
|
8.37 | 4.97 | 5.82 |
|
6.65 | 13.91 | 7.08 |
|
12.86 | 5.69 | 5.13 |
|
5.42 | 8.18 | 5.82 |
These haplogroups (excluding R0a) correspond to those tested in the logistic regression models.
Power percentages were calculated as reported in
H here includes H*, H8 and H9 of
HV here includes HV* and HV0 of
In brief, our study provides important clues indicating that certain mtDNA haplogroups might modulate diabetes complications. Obviously to definitively link mtDNA backgrounds with T2DM complications additional studies at the same level of phylogenetic resolution in other populations with similar haplogroup/subhaplogroup profiles are required. It is also likely that for many uncommon subhaplogroups only meta-analyses encompassing data from multiple studies will be able to reach power values that are adequate to provide definitive answers on the issue.
All experimental procedures and written informed consent, obtained from all donors, were reviewed and approved by the Ethics Committee of the National Institute on Health and Science on Aging (INRCA), Ancona, Italy, in accordance with the European Union Directive 86/609.
A sample of 904 unrelated subjects (433 males and 471 females) age 40 years and older was collected by the Diabetology Unit, INRCA (National Institute on Health and Science on Aging) in Ancona (Italy). This included 466 patients affected with T2DM – whose diagnosis was made according to the American Diabetes Association Criteria (
The basic phenotypical and clinical characteristics (including data on vital signs, anthropometric factors, medical history, behavior and lifestyle, etc.) of the sample are summarized in
Hypertension was defined as a systolic blood pressure >140 mmHg and/or a diastolic blood pressure >90 mmHg. The values were measured while the subjects were sitting and confirmed at least three times. Overnight fasting venous blood samples from all subjects were collected from 8:00 to 9:00 a.m. The biological samples were either analyzed immediately or stored at −80°C for no more than ten days. Blood concentrations for HDL cholesterol, triglycerides, HbA1c, fasting insulin, fibrinogen, high-sensitivity C reactive protein (hsCRP), creatinine, urea nitrogen, and white blood cells count were measured by standard procedures.
Total DNA was extracted from peripheral blood using standard commercial kits (Qiamp DNA Blood Maxi Kit, Qiagen) and stored at −20°C. The mtDNA from the 904 subjects was first analyzed by sequencing ∼800 bp from the control region for each subject (at least from nucleotide position [np] 16024 to np 220), thus including the entire hypervariable segment [HVS]-I [nps 16024–16383] and part of the HVS-II [nps 57–372]. The GenBank accession numbers for the 904 mtDNA control-region sequences are JF716451-JF717354. This analysis was followed by a hierarchical survey of haplogroup and sub-haplogroup diagnostic markers in the coding region, which allowed the classification of mtDNAs into different haplogroups and sub-haplogroups
Sequencing of entire mtDNA genomes (belonging to haplogroups R0a and H3) and phylogenetic analysis were performed as previously described
Statistical analyses were performed using the SPSS statistical package. Quantitative clinical data were compared between patients with diabetes and control individuals by the unpaired Student's
Binary logistic regressions were used to determine, simultaneously across the whole sample, whether the susceptibility to develop T2DM or T2DM complications – represented by binary dependent variables (or outcomes) taking on values 0 and 1) – differed among haplogroups. This approach reduces the chance of type I error (false-positive result) and controls for differences in the frequency of key variables among the different groups. MtDNA haplogroups are phylogenetically related, but they are also defined by different clusters of haplotype-specific polymorphisms. Thus, the categorical variable "haplogroup" is converted into different dummy variables (or predictors, one for each haplogroup) and introduced separately into the regression equation. To avoid small sample sizes, some of the haplogroups were grouped following phylogenetic considerations, whenever possible. The threshold was established at >10 subjects across the whole patients’ group, in keeping with the “rule of thumb” whereby logistic regression should be performed only when the number of studied subjects is one order of magnitude greater than each parameter. Thus, the uncommon haplogroups H8 and H9 went into H (together with H*); HV0 was grouped with the sister paragroup HV*; U4 and U9 were clustered together; U8b, K1 and K2 were considered as U8b/K; R0a, W, the remaining U subclades (namely U1, U2, U6 and U7), and the African/Asian haplogroups were not included in the logistic computation. After this correction, 16 (haplogroup) classes were obtained. To find out how these combined predictors affect the outcome variable (T2DM or T2DM complications) we used a stepwise forward method with the likelihood ratio (LR) test employed for entering the terms (probability thresholds: entry 0.05, since we have modeled two outcomes i.e. T2DM and T2DM complications; removal 0.100): the initial model contained only the constant (ß0); then the program searched for the predictor which has the highest simple correlation with the outcome variable; if this significantly improved the model, it was retained; then the program searched for the predictor which has the second highest semi-partial correlation with the outcome; if this significantly improved the model, it was retained, and so on. The chi-squared significance of the obtained model was computed by calculating the difference between log-likelihood statistic (-2LL) of the final block and that of the first step. Since we have modeled 16 haplogroups only the model
In order to verify the relationship between mitochondrial haplogroups and T2DM complications we applied a decision tree analysis. In particular, the significant groupings in the logistic analyses (i.e. H3, H, U3 and V) were tested as predictors by Chi-squared Automatic Interaction Detection (CHAID)
Power values for each haplogroup were calculated by following the procedure previously described by Samuels et al.
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The authors thank Norman Angerhofer (Sorenson Molecular Genealogy Foundation, Utah, USA) for providing bioinformatics support and Alessia Grinzato (University of Pavia) for helping with experimental work.