BUG: uint32 is not being preserved while round-tripping through parquet file
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
In[42]: df = pd.DataFrame({'a':pd.Series([1, 2, 3], dtype="uint64")})
In[43]: df.to_parquet('a')
In[44]: pd.read_parquet('a').dtypes
Out[44]: 
a    uint64
dtype: object
In[45]: df = pd.DataFrame({'a':pd.Series([1, 2, 3], dtype="uint32")})
In[46]: df.to_parquet('a')
In[47]: pd.read_parquet('a').dtypes
Out[47]: 
a    int64
dtype: object

```

#### Problem description

It appears to be that `uint32` is not being preserved like `uint64` is being preserved while round-tripping through a parquet file.

#### Expected Output

Preserve the `uint32` dtype.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.7.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-52-generic
Version          : #57-Ubuntu SMP Thu Oct 15 10:57:00 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 49.6.0.post20201009
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : 5.37.3
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.4
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

</details>

Crosslinking to cudf fuzz-testing for tracking purpose: https://github.com/rapidsai/cudf/issues/6001